JP2000123153A - Image processor - Google Patents

Abstract

PROBLEM TO BE SOLVED: To enable high-speed color converting processing even while using a software by calculating the reference address of lattice point data at a lattice point to become a reference, reading lattice point data required for the interpolating operation of a convert point from that reference address and performing the interpolating operation of the converting point. SOLUTION: When respective high-order 4 bits of an RGB signal at a converting point P are defined as RH GH and BH, in the order of lattice points, the lattice point data of eight lattice points 'A to H' are respectively stored for each CMYK. In this case, when the reference point of the lattice point 'A' in a component 'C' is determined, the reference addresses of lattice points 'A to H' can be provided only by successive increment. Next, weight coefficients W (w1-w8) regardless of 'C, M, Y and K' components are continuously stored. In this case, when the reference address of the weight coefficient w1 is known, all the weight coefficients W (w1-w8) can be successively provided only by incrementing them seven times.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image processing apparatus, and more particularly, to a "color system" which handles "primary colors (R, G, B) of light" handled by a color scanner, a color monitor, and color image data by a color printer or the like. Three primary colors (C, M, Y
(, K))).

[0002]

2. Description of the Related Art In recent years, with computers, anyone can easily handle color images on a screen. The color image is easily input and output between various devices. By the way, when each signal of the three primary colors (R, G, B) of light read by the color scanner is recorded on a recording paper by a color printer, each signal of the three primary colors (C, M, Y (, K)) of each color is used. Must be converted to In televisions and displays, various colors can be expressed by combinations of the three primary colors of light (R, G, B). In this method, various colors are added by adding three colors from a state where none of the colors shine (all 0: black) to a state where all the colors shine (all 100: white). It is called additive color mixing (addition color method) to express.

However, a color can be expressed by additive color mixture when it can emit light by itself. Therefore, when no light is emitted by itself, for example, when recording is performed on recording paper, the color is expressed by the reflected light. To be more precise, a color is expressed by absorbing (subtracting) a part of the color of the applied light and reflecting the remaining color. Such a method is called subtractive color mixing (subtraction method),
Ink and paint express various colors by the subtractive color mixture.

In the subtractive color mixture, the basic color is not the additive color mixture of red (R), green (G), and blue (B), but a mixture of cyan (color that does not reflect any light) when mixed. C), magenta (M), and yellow (Y). Here, theoretically, if three colors of C, M, and Y are mixed,
"Black", but in order to express "Black" more clearly,
A method of recording in four colors of C, M, Y, and K using black (K) ink is generally performed. By the way, conventionally, in the color conversion processing from RGB signals to CMYK signals,
An interpolation operation method is used. The interpolation calculation is executed by hardware because high-speed processing is required.

[0005]

However, when the interpolation processing is implemented by hardware, a dedicated LSI is required, the circuit becomes complicated, and it is not possible to reduce the size and cost of the LSI. In addition, since it is configured by hardware, a dedicated circuit is required, and there is a problem that it is not possible to cope with various interpolation calculation methods. On the other hand, in recent years, since the processing speed of the MPU has been improved, it has become possible to perform interpolation calculation at high speed using software. However, since the required processing speed of the color printer has been improved, it is necessary to perform the color conversion processing faster than the processing speed of the color printer. SUMMARY OF THE INVENTION The present invention has been made to meet such a demand in the market, and an object of the present invention is to provide an image processing apparatus capable of performing high-speed color conversion processing using software.

[0006]

In order to achieve the above object, according to the first aspect of the present invention, in an image processing apparatus for converting a color space, at least grid point data of grid points surrounding a conversion point is calculated. Storage means for successively storing data in a necessary order, and calculating a reference address of grid point data at a grid point serving as a reference, and sequentially incrementing from the reference address to obtain grid points required for interpolation calculation of conversion points. Control means for reading out the data and performing an interpolation operation of the conversion point.

According to a second aspect of the present invention, in the image processing apparatus of the first aspect, the storage means stores whether or not the exception processing is performed, and the control means determines whether the exception processing is performed. Interpolation of the conversion point is performed according to the case where it does not apply.

According to a third aspect of the present invention, in the image processing apparatus according to the first aspect, the control unit performs the interpolation operation of the conversion point without determining whether the exception processing is performed.

In the embodiments of the invention described below, the "storage means" described in the claims or the means for solving the problems corresponds to the ROM 12, and the "control means" is also the MPU 11, the ROM 12 and the ROM 12. RAM 13
Is equivalent to

[0010]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS [First Embodiment] Cubic Interpolation (8-Point Interpolation) A first embodiment in which the present invention is embodied in a facsimile apparatus will be described below with reference to the drawings.

As shown in FIG. 1, a facsimile apparatus 1 as an image processing apparatus includes an MPU 11, a ROM 12,
M13, a reading unit 14, a recording unit 15, an operation unit 16, a display unit 17, an image memory 18, a codec 19, a modem 20, and an NCU 21.
Are connected via a bus 22.

The MPU 11 controls each part of the facsimile machine 1. The ROM 12 stores a program for controlling the facsimile machine 1. Also, RO
M12 stores various data necessary for the interpolation operation. Specifically, a lookup table (Look-Up Table; LUT for short) shown in FIG.
The LUT of the weight coefficient W (w1 to w8) shown in FIG.
The RAM 13 temporarily stores various data relating to the facsimile machine 1. The reading unit 14 includes a color scanner, reads image data on a document, and outputs RGB signals.

The recording unit 15 is composed of an electrophotographic color printer, a thermal printer, or an ink jet type color printer, and stores received image data and image data of a document read by the reading unit 14 on recording paper in a copying operation. Record. The operation unit 16 includes a numeric keypad (including the * and # keys) 16a for inputting a facsimile number or the like, an abbreviated key 16 for registering an abbreviated number, and transmitting from the abbreviated number.
b, various operation keys such as a start key 16c for starting a document reading operation, and a communication / copy key 16d for setting a “communication (FAX)” operation or a “copy” operation. A display unit 17 such as an LCD displays various information such as an operation state of the facsimile machine 1.

The image memory 18 temporarily stores received image data and image data read by the reading unit 14 and compression-coded by the codec 19 in the MH, MR, or MMR system. The codec 19 encodes the image data read by the reading unit 14 by MH, MR, or MMR for transmission. The codec 19 decodes the received image data. The modem 20 conforms to ITU-T Recommendation T.30. 30 based on a facsimile transmission control procedure according to V.30. 17, V. 27te
r, V. Modulation and demodulation of transmission / reception data in accordance with any one of E.29 and the like. The NCU 21 has a function of controlling connection with the telephone line L and detecting transmission and reception of a dial signal corresponding to a fax number of the other party.

Next, a description will be given of a color conversion process by an interpolation operation method using a look-up table (LUT).
First, cubic interpolation (8-point interpolation) will be described with reference to the drawings. The RGB signals output from the reading unit 14 are each composed of 8 [bit] data.
Therefore, each of the RGB signals has 256 gradation data.

As shown in FIG. 2, in the RGB space,
When each lower 4 bits of the RGB signal, that is, each axis is divided into 16, the number of intersections between each axis and each grid point is “1”.
7 ". In other words, the intersection between each axis and each grid point is
"0, 16, 32, ..., 240, 255".
Here, when the intersection between each axis and each grid point is represented by a hexadecimal number, "00h, 10h, 20h, ..., F0h, FF
h ". “H” indicates a hexadecimal number. same as below.

That is, "0-240 (00h-F0
h)), every 16 increments will be an intersection,
"15" up to "240-255 (F0h-FFh)"
When it increases, it becomes an intersection. Therefore, if each grid point data corresponding to the RGB signal is stored in advance as a “three-dimensional LUT”, in the case of an RGB signal corresponding to the grid point,
Color conversion processing can be quickly performed from grid point data without any calculation.

However, in actual color conversion processing, it is extremely rare that a conversion point corresponds to a grid point. For this reason, when a conversion point does not correspond to a grid point, an interpolation operation is performed based on grid point data of a grid point in a cube surrounding the conversion point. Therefore, the upper 4 bits of the RGB signal at the conversion point are set to (RH, GH, B
H), it is possible to determine in which cube the conversion point is located based on each value of (RH, GH, BH).

Therefore, as shown in FIG. 3, "C, M,
L in which each grid point data corresponding to the “Y, K” components is stored.
Assume UT. That is, "C" component, "M" component,
The upper 4 bits of the RGB signal at the conversion point P corresponding to the “Y” component and the “K” component in the order of (R)
H, GH, BH), (0, 0, 0), (1,
(0,0), (2,0,0),..., (16,16,1)
5) In this case, grid point data is stored in the order of (16, 16, 16) grid points.

Here, as shown in FIG. 4, the color image data output from the reading unit 14, that is, the conversion point indicated by the RGB signal is "P", and each grid point of the cube surrounding the conversion point P Let “A to H” be the reference addresses HADR (N) of the grid point data in the “C” component (where N is the same) in each grid point data in the “C, M, Y, K” components shown in FIG. = A to H) can be shown as follows.

HADR (A) = (RH) + (GH) * 17 + (BH) * 17 ^ 2 (Equation 1-1) HADR (B) = (RH) + (GH) * 17 + ( BH + 1) * 17 ^ 2 = (RH) + (GH) * 17 + (BH) * 17 ^ 2 + 17 ^ 2 = HADR (A) +289 ............ (Formula 1-2) HADR (C) = (RH) + (GH + 1) * 17 + (BH) * 17 ^ 2 = (RH) + (GH) * 17 + (BH) * 17 ^ 2 + 17 = HADR (A) +17 ……… (Equation 1-3) HADR (D) = (RH) + (GH + 1) * 17 + (BH + 1) * 17 ^ 2 = (RH) + (GH) * 17 + (BH) * 17 ^ 2 + 17 + 17 ^ 2 = HADR (A) +306 ...... (Equation 1-4) HADR (E) = (RH + 1) + (GH) * 17 + (BH) * 17 ^ 2 = (RH) + (GH) * 17 + (BH) * 17 ^ 2 + 1 = HADR (A) +1 ... (Equation 1-5)

HADR (F) = (RH + 1) + (GH) * 17 + (BH + 1) * 17 ^ 2 = (RH) + (GH) * 17 + (BH) * 17 ^ 2 + 1 + 17 ^ 2 = HADR (A) +290 ...... (Equation 1-6) HADR (G) = (RH + 1) + (GH + 1) * 17 + (BH) * 17 ^ 2 = (RH) + (GH) * 17 + (BH) * 17 ^ 2 + 1 + 17 = HADR (A) +18 ...... (Equation 1-7) HADR (H) = (RH + 1) + (GH + 1) * 17+ (BH + 1) * 17 ^ 2 = (RH) + (GH) * 17 + (BH) * 17 ^ 2 + 1 + 17 + 17 ^ 2 = HADR (A) +307 ............ (Equation 1 -8) Note that “*” indicates multiplication and “＾” indicates power. Less than,
the same.

Here, the grid point "A" in the "C" component
Considering the offset to the next component “M, Y, K” with reference to the following equation, the offset M (os) to the next component “M” is obtained.
Can be shown as follows. M (os) = 17 ^ 3 = 4913 (Equation 1-9) Also, the offset Y (os) to the next component "Y" can be expressed as follows. Y (os) = 17 ^ 3 * 2 = 4913 * 2 = 9826 (Equation 1-10) Further, the offset K (os) to the next component "K" can be expressed as follows. K (os) = 17 ^ 3 * 3 = 4913 * 3 = 14739 ............ (Equation 1-11)

For this reason, as shown in FIG. 3, when the grid point data is stored, the above (Equation 1-2) to (Equation 1-8)
As is clear from FIG. 7, when the reference address of the grid point “A” in the “C” component is used as a reference, the grid points “B to
H, the offset of the reference address is the grid point “B”.
~ H ". Therefore, in order to obtain the grid point data of the grid points “B to H”, the address must be calculated for each grid point. In addition, the formulas (1-9) to
As is clear from (Equation 1-11), the next component “M,
The reference address of the grid point “A” in “Y, K” also differs by the next component “M, Y, K” from the reference address of the grid point “A” in the reference “C” component. Therefore, in order to obtain grid point data of the grid points “A to H” in the next component “M, Y, K”, the address is calculated every time the next component “M, Y, K” is changed. There must be.

Therefore, as shown in FIG. 5, the upper 4 bits of the RGB signal at the conversion point P are represented by (RH, GH,
BH), (0,0,0), (1,0,0),
(2, 0, 0), ..., (15, 15, 14), (1
5, 15, 15), the grid point data of eight grid points "A to H" is stored for each CMYK. Specifically, for (0, 0, 0), grid point data of grid points “A to H” in “C” component, grid point data of grid points “A to H” in “M”, “ The grid point data of the grid points “A to H” in the “Y” component and the grid point data of the grid points “A to H” in the “K” component are stored.

Subsequently, for (1, 0, 0), "C"
Grid point data of grid points "A to H" in the component, "M"
Grid point data of grid points "A to H" in the component, "Y"
Grid point data of grid points "A to H" in the component, "K"
The grid point data of the grid points “A to H” in the component is stored. And finally, for (15,15,15),
Grid point data of grid points “A to H” in the “C” component;
Grid point data of grid points “A to H” in the “M” component;
Grid point data of grid points “A to H” in the “Y” component;
The grid point data of the grid points “A to H” in the “K” component is stored.

By storing in this way, the grid point data to be stored increases, but the grid point "A" in the "C" component is stored.
Is determined, the reference addresses of the lattice points "A to H" can be obtained only by sequentially incrementing the reference addresses. In other words, by sequentially incrementing from the reference address HADR (A) of the grid point “A” in the “C” component, grid point data of the grid points “A to H” can be obtained. More specifically, when the reference address HADR (A) of the grid point “A” in the “C” component is incremented seven times, all grid point data in the “C” component can be obtained. Subsequently, when the increment is performed eight times, all grid point data in the “M” component can be obtained. In addition, when the increment is performed eight times, all the grid point data in “Y” can be obtained. Further, when the increment is performed eight times, all the grid point data at “K” can be obtained.

Therefore, the grid point "A" in the "C" component
If the reference address HADR (A) is known, all the grid point data in the "C, M, Y, K" components can be sequentially obtained by incrementing the reference address HADR (A) 31 times. For this reason, (RH, GH,
As (BH) grid point data, (0, 0, 0) to (1)
Instead of the grid point data up to (6, 16, 16), (0,
It is only necessary to store the grid point data from (0,0) to (15,15,15).

Thus, by storing the grid point data as shown in FIG. 5, the reference address HADR (A) of the grid point "A" in the "C" component can be represented as follows. HADR (A) = (RH + GH * 16 + BH * 16 ^ 2) * 4 * 8 = (RH + GH * 16 + BH * 256) * 32 (Equation 2-1) Further, "C" The reference address HADR (N) (where N = B to H) of the grid point “B to H” in the component can be represented as follows. HADR (B) = (RH + GH * 16 + BH * 16 ^ 2) * 4 * 8 + 1 = HADR (A) +1 ...... (Equation 2-2) HADR (C) = (RH + GH * 16 + BH * 16 ^ 2) * 4 * 8 + 2 = HADR (A) +2 ... (Equation 2-3) HADR (D) = (RH + GH * 16 + BH * 16 ^ 2) * 4 * 8 + 3 = HADR (A) +3 (Equation 2-4)

HADR (E) = (RH + GH * 16 + BH * 16 ^ 2) * 4 * 8 + 4 = HADR (A) +4 (Expression 2-5) HADR (F) = (RH + GH * 16 + BH * 16 ^ 2) * 4 * 8 + 5 = HADR (A) +5 ... (Equation 2-6) HADR (G) = (RH + GH * 16 + BH * 16 ^ 2 ) * 4 * 8 + 6 = HADR (A) +6 ... (Equation 2-7) HADR (H) = (RH + GH * 16 + BH * 16 ^ 2) * 4 * 8 + 7 = HADR ( A) +7 (Equation 2-8) Hereinafter, similarly, the grid points “A to
H ", the reference address HADR (N) (where N = A to
H) can also be shown using an expression representing the increment.

Next, the principle of interpolation in cubic interpolation will be described with reference to the drawings. As shown in FIG. 6A, assuming that the conversion point indicated by the color image data output from the reading unit 14, that is, the RGB signal is “P”, the cube is formed based on the conversion point P. It can be divided into eight rectangular parallelepipeds (eight cubes when the conversion point P is located at the center of the cube). Therefore, FIG.
As shown in (b), the volume of the obtained eight rectangular parallelepipeds is represented by w
If 1 to w8, the interpolation value IPL (C) of the “C” component at the conversion point P can be expressed as follows. IPL (C) = (w1 * c8 + w2 * c7 + w3 * c6 + w4 * c5 + w5 * c4 + w6 * c3 + w7 * c2 + w8 * c1) / (w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8) (Equation 3-1) Note that “c1 to c8” are the “C” components obtained by the increment based on the reference address HADR (A) of the (Equation 2-1). This is grid point data of grid points “A to H”.

The "M" component at the conversion point P,
Interpolated values IPL (M), IPL of “Y” component, “K” component
(Y) and IPL (K) can be similarly expressed as follows. IPL (M) = (w1 * m8 + w2 * m7 + w3 * m6 + w4 * m5 + w5 * m4 + w6 * m3 + w7 * m2 + w8 * m1) / (w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8) ...... (Equation 3-2) IPL (Y) = (w1 * y8 + w2 * y7 + w3 * y6 + w4 * y5 + w5 * y4 + w6 * y3 + w7 * y2 + w8 * y1) / (w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8) ............ (Equation 3-3) IPL (K) = (w1 * k8 + w2 * k7 + w3 * k6 + w4 * k5 + w5 * k4 + w6 * k3 + w7 * k2 + w8 * k1) / (w1 + w2 + w3 + w4 + w5 + w6 + w7 + w8) ... (Equation 3-4)

Note that “m1 to m8”, “y1 to y8”, and “k1 to k8” are also obtained by incrementing “M, Y, Y” based on the reference address HADR (A) of the above (Equation 2-1). K is grid point data of grid points “A to H” in “K”. As described above, the interpolation values IPL (N) (where N = C, M, Y, K) of the “C, M, Y, K” components are evident from (Equation 3-1) to (Equation 3-4). In this way, the volume w1 to w8 of the rectangular parallelepiped is the “weight coefficient W” in the interpolation value IPL (N). And "C, M, Y, K"
The weighting factors W (w1 to w8) used when calculating the component interpolation value IPL (N) are all the same. In other words, the weight coefficient W is independent of the “C, M, Y, K” components.

Therefore, the weight coefficients W (w1 to w8) irrelevant to the "C, M, Y, K" components are continuously stored. That is, as shown in FIG. 7, the data of the color image output from the reading unit 14, that is, the RGB data at the conversion point P
Assuming that each lower 4 bits of the signal is (RL, GL, BL), (0, 0, 0), (1, 0, 0), (2, 0,
0),..., (15, 15, 14), (15, 15,
15) In order of each grid point, the corresponding weight coefficient W
(W1 to w8) are stored continuously.

Specifically, a weight coefficient W (w1 to w8) is stored for (0, 0, 0). Then, (1,
A weight coefficient W (w1 to w8) is stored for (0, 0). And finally, for (15,15,15),
The weight coefficients W (w1 to w8) are stored. Therefore, the reference address LADR (w1) of the weight coefficient w1 can be represented as follows. LADR (w1) = (RL + GL * 16 + BL * 16 ^ 2) * 8 = (RL + GL * 16 + BL * 256) * 8 (Equation 4-1) Also, weighting factors w2 to w8 Reference address of LADR
(N) (where N = w2 to w8) can be shown as follows. LADR (w2) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + 1 = LADR (w1) +1 ............ (Formula 4-2) LADR (w3) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + 2 = LADR (w1) +2 ............ (Equation 4-3) LADR (w4) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + 3 = LADR (w1) +3 (Equation 4-4)

LADR (w5) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + 4 = LADR (w1) +4 (Equation 4-5) LADR (w6) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + 5 = LADR (w1) +5 ............ (Equation 4-6) LADR (w7) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + 6 = LADR (w1) +6 ...... (Equation 4-7) LADR (w8) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + 7 = LADR (w1) +7 ............ ( (Equation 4-8) Therefore, if the reference address LADR (w1) of the weighting factor w1 is known by storing as above, all the weighting factors W (w1 to w8) can be sequentially obtained only by incrementing seven times. it can. Similarly, the reference address LAD of the weight coefficient W (w1 to w8) in “M, Y, K”
R (N) (where N = w1 to w8) can also be represented by an expression representing the increment.

Next, the interpolation value I of the "C, M, Y, K" components
A method of calculating PL (N) (where N = C, M, Y, K) will be described. Assuming that the lower 4 bits of the color image data at the conversion point P, that is, the lower 4 bits of the RGB signal at the conversion point P are (RL, GL, BL),
Interpolated value IPL (N) of “C, M, Y, K” components (however,
N = C, M, Y, K) are expressed by (Equation 3-1) to (Equation 3-4).
Thus, it can be shown as follows. IPL (N) = (w1 * f (HADR (A)) + w2 * f (HADR (B)) + w3 * f (HADR (C)) + w4 * f (HADR (D)) + w5 * f ( HADR (E)) + w6 * f (HADR (F)) + w7 * f (HADR (G)) + w8 * f (HADR (H))} / (16 * 16 * 16) ............ (Equation 5 )

Note that f (HADR) shown in (Equation 5)
(N)) (however, N = A to H) are obtained by incrementing “C, M,
This is grid point data of grid points “A to H” in the “Y, K” components.

Here, as shown in FIG. 6B,
The volumes of the eight rectangular parallelepipeds based on the conversion point P, that is, the weighting factors W (w1 to w8) are assigned to the lower 4 bits of the RGB signal [bi
t], that is, (RL, GL, BL) can be expressed as follows. w1 = (16-RL) * (16-GL) * (16-BL) ... (Equation 6-1) w2 = (16-RL) * (16-GL) * BL ... (Equation 6) 2) w3 = (16-RL) * GL * (16-BL) (Equation 6-3) w4 = (16-RL) * GL * BL (Equation 6-4) w5 = RL * (16-GL) * (16-BL) ... (Equation 6-5) w6 = RL * (16-GL) * BL ... (Equation 6-6) w7 = RL * GL * (16-BL) ) ............ (Equation 6-7) w8 = RL * GL * BL ............ (Equation 6-8)

Therefore, the above (Equation 5) is replaced by (Equation 6-1) to
Substituting (Equation 6-8), the interpolation value IPL (N) (where N = C, M, Y, K) of the “C, M, Y, K” component is
It can be shown as follows. IPL (N) = {(16-RL) * (16-GL) * (16-BL) * f (HADR (A)) + (16-RL) * (16-GL) * BL * f (HADR ( B)) + (16-RL) * GL * (16-BL) * f (HADR (C)) + (16-RL) * GL * BL * f (HADR (D)) + RL * (16-GL ) * (16-BL) * f (HADR (E)) + RL * (16-GL) * BL * f (HADR (F)) + RL * GL * (16-BL) * f (HADR (G) ) + RL * GL * BL * f (HADR (H))} / (16 * 16 * 16) (7) where f (HADR (N)) shown in (7) (where N
= A to H) is the grid point data of the grid points “A to H” in the “C, M, Y, K” components obtained by the increment based on the above (Equation 2-1).

Next, a case where the conversion point P corresponds to exception processing in cubic interpolation will be described. In the RGB space shown in FIG. 2, each of the RGB signals is 8 [bi
t], each axis is “0-255 (00
h to FFh) ”. For this reason, 16
When divided, they are not all at the same interval. In other words, in each axis, the intersection becomes a point every time "16" is increased from "0 to 240 (00h to F0h)".
55 (F0h to FFh) "becomes an intersection when" 15 "is increased. For this reason, the size for performing the interpolation calculation is “2”.
40 to 255 (F0h to FFh) ".

Therefore, the conversion point P is set to "240 to 255 (F
0h to FFh) ”must be determined. However, in the case where the interpolation calculation is configured by software, the interpolation calculation processing is performed after determining whether or not the conversion point P corresponds to the exception processing. Since the process of determining whether or not an exception process is performed is performed for all pixels, the determination process is performed for a large number of pixels even if the time required for the determination process for one pixel is very small. If so, it takes a long time for the determination process. Therefore, as shown in FIG.
Consider a case that corresponds to exception processing in a cube in the GB space. That is, the case corresponding to the exception processing means that the upper 4 bits of the RGB signal at the conversion point P are set to (R
H, GH, BH), (RH, GH, BH)
Is “15”.

Therefore, when the conversion point P corresponds to the exception processing, the following “seven cases” are performed. [1] RH = 15, GH <15, BH <15 (E1 shown in FIG. 8) [2] RH <15, GH = 15, BH <15 (E2 shown in FIG. 8) [3] RH <15, GH <15, BH = 15 (E3 shown in FIG. 8) [4] RH = 15, GH = 15, BH <15 (E4 shown in FIG. 8) [5] RH <15, GH = 15, BH = 15 (FIG. 8) [6] RH = 15, GH <15, BH = 15 (E6 shown in FIG. 8) [7] RH = 15, GH = 15, BH = 15 (E7 shown in FIG. 8)

For this reason, the weighting factors W (w1 to w8) in the cases corresponding to the exceptional processes [1] to [7] are
From the above (Formula 6-1) to (Formula 6-8), they can be shown as follows. [1] When RH = 15, GH <15, BH <15 (E1 shown in FIG. 8) w1 = (15-RL) * (16-GL) * (16-BL) (Equation 8-1) ) W2 = (15-RL) * (16-GL) * BL (Equation 8-2) w3 = (15-RL) * GL * (16-BL) ... (Equation 8-3) w4 = (15-RL) * GL * BL ... (Equation 8-4) w5 = RL * (16-GL) * (16-BL) ... (Equation 8-5) w6 = RL * (16- GL) * BL ...... (Equation 8-6) w7 = RL * GL * (16-BL) ...... (Equation 8-7) w8 = RL * GL * BL ...... (Equation 8-8)

[2] When RH <15, GH = 15, BH <15 (E2 shown in FIG. 8) w1 = (16-RL) * (15-GL) * (16-BL) (Expression 9-1) w2 = (16-RL) * (15-GL) * BL (Equation 9-2) w3 = (16-RL) * GL * (16-BL) (Equation 9- 3) w4 = (16-RL) * GL * BL (Equation 9-4) w5 = RL * (15-GL) * (16-BL) ... (Equation 9-5) w6 = RL * (15-GL) * BL ... (Equation 9-6) w7 = RL * GL * (16-BL) ... (Equation 9-7) w8 = RL * GL * BL ... (Equation 9-6) 8)

[3] When RH <15, GH <15, BH = 15 (E3 shown in FIG. 8) w1 = (16-RL) * (16-GL) * (15-BL) 10-1) w2 = (16-RL) * (16-GL) * BL (Equation 10-2) w3 = (16-RL) * GL * (15-BL) (Equation 10- 3) w4 = (16-RL) * GL * BL (Equation 10-4) w5 = RL * (16-GL) * (15-BL) ... (Equation 10-5) w6 = RL * (16-GL) * BL (Equation 10-6) w7 = RL * GL * (15-BL) (Equation 10-7) w8 = RL * GL * BL (Equation 10-6) 8)

[4] When RH = 15, GH = 15, BH <15 (E4 shown in FIG. 8) w1 = (15-RL) * (15-GL) * (16-BL) (Equation 4) 11-1) w2 = (15-RL) * (15-GL) * BL (Equation 11-2) w3 = (15-RL) * GL * (16-BL) (Equation 11- 3) w4 = (15-RL) * GL * BL (Equation 11-4) w5 = RL * (15-GL) * (16-BL) (Equation 11-5) w6 = RL * (15-GL) * BL ... (Equation 11-6) w7 = RL * GL * (16-BL) ... (Equation 11-7) w8 = RL * GL * BL ... (Equation 11-6) 8)

[5] When RH <15, GH = 15, BH = 15 (E5 shown in FIG. 8) w1 = (16-RL) * (15-GL) * (15-BL) (Equation 5) 12-1) w2 = (16-RL) * (15-GL) * BL (Equation 12-2) w3 = (16-RL) * GL * (15-BL) (Equation 12- 3) w4 = (16-RL) * GL * BL (Equation 12-4) w5 = RL * (15-GL) * (15-BL) ... (Equation 12-5) w6 = RL * (15-GL) * BL ... (Equation 12-6) w7 = RL * GL * (15-BL) ... (Equation 12-7) w8 = RL * GL * BL ... (Equation 12-6) 8)

[6] When RH = 15, GH <15, BH = 15 (E6 shown in FIG. 8) w1 = (15-RL) * (16-GL) * (15-BL) (Equation 5) 13-1) w2 = (15-RL) * (16-GL) * BL (Equation 13-2) w3 = (15-RL) * GL * (15-BL) (Equation 13- 3) w4 = (15-RL) * GL * BL (Equation 13-4) w5 = RL * (16-GL) * (15-BL) ... (Equation 13-5) w6 = RL * (16-GL) * BL ... (Equation 13-6) w7 = RL * GL * (15-BL) ... (Equation 13-7) w8 = RL * GL * BL ... (Equation 13-6) 8)

[7] When RH = 15, GH = 15, BH = 15 (E7 shown in FIG. 8) w1 = (15-RL) * (15-GL) * (15-BL) 14-1) w2 = (15-RL) * (15-GL) * BL (Equation 14-2) w3 = (15-RL) * GL * (15-BL) (Equation 14- 3) w4 = (15-RL) * GL * BL (Equation 14-4) w5 = RL * (15-GL) * (15-BL) ... (Equation 14-5) w6 = RL * (15-GL) * BL ... (Equation 14-6) w7 = RL * GL * (15-BL) ... (Equation 14-7) w8 = RL * GL * BL ... (Equation 14-6) 8)

Next, a method of determining whether the conversion point P corresponds to exception processing will be described. The upper 4 bits of the RGB signal at the conversion point P are represented by (RH, GH, B
H), it may be configured to determine whether any of the values of (RH, GH, BH) is “15” and perform the interpolation calculation process. However, in order to perform the interpolation arithmetic processing at a higher speed, and thus to improve the processing speed of the entire apparatus, a case where (RH, GH, BH) corresponds to an exception process and a case where it does not correspond to an exception process Is stored as (RH, GH, BH).

That is, as shown in FIG. 9, if each of the upper 4 bits of the RGB signal is (RH, GH, BH) and the value indicating whether or not the exception processing is performed is "Z", In the case of [1] to [7] corresponding to the exception processing of
If the value of “Z” is “1 to 7” and the case does not correspond to the exception processing, that is, each of the values of (RH, GH, BH) is “1”
If it is not "5", in other words, if all the values of (RH, GH, BH) are "0 to 14", the value of "Z" is stored as "0". For this reason, whether or not an exception is handled can be determined based on (RH, GH, BH) based on the value “Z” indicating whether or not the exception is handled. In addition, it is possible to determine which of the “seven kinds” of the exceptional processes shown in [1] to [7] corresponds to the exceptional process.

Therefore, the reference address ZHADR (Z) of “Z” indicating whether or not the exception processing is performed is (RH, G
H, BH), it can be expressed as follows. ZHADR (Z) = RH + GH * 16 + BH * 16 ^ 2 = RH + GH * 16 + BH * 256 ... (Equation 15)

Next, another method for determining whether or not the conversion point P corresponds to exception processing will be described. That is,
In “seven kinds” of exception processing shown in [1] to [7],
[1] When RH = 15, GH <15, BH <15 Z = 1 [2] RH <15, GH = 15, BH <15 If Z = 2 [3] RH <15, GH <15, BH = 15 Z = 4 [4] If RH = 15, GH = 15, BH <15 Z = 3 [5] RH <15, GH = 15, BH = 15 Z = 6 [6] RH = 15, GH <15, BH = 15 Z = 5 [7] RH = 15, GH = 15, BH = 15 Z = 7 Is defined in advance, the value “Z” indicating whether or not the exception processing is applicable can be indicated as follows. Z = (RH == 15) + (GH == 15) * 2 + (BH == 15) * 4 (Equation 15-1) Here, “RH == 15” means that RH = 15. Is defined as "1" in the case of, and "0" in the case of RH ≠ 15. In addition,
“GH == 15” and “BH == 15” are also equivalent to “RH ==
15 ".

Next, the order of storing the weighting factors W (w1 to w8) in the case of exception processing will be described with reference to the drawings. As shown in FIG. 10, the value indicating whether or not the exception processing is applied is “Z”, and the data of the color image output from the reading unit 14, that is, each of the lower 4 bits of the RGB signal is (RL, GL). , BL), the weighting factor is “W”, and (RL, G) corresponding to each Z (= 0 to 7)
(L, BL). Also, (RL, GL, BL)
Are successively stored in the order of w1 to w8.

More specifically, for (0, 0, 0) in the case where Z = "0", a weight coefficient W (w1 to w8) is stored. Subsequently, a weighting coefficient W (w1 to w8) is stored for (1, 0, 0). And finally, Z
Weight coefficients W (w1 to w8) are stored for (15, 15, 15) in the case of = “7”.

For this reason, the reference address ELADR (w1) of the weight coefficient w1 including the case corresponding to the exception processing can be expressed as follows. ELADR (w1) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 8 = (RL + GL * 16 + BL * 256) * 8 + Z * 4096 * 8 …… (Equation 16-1) Also, the weighting factors w2 to w including the case corresponding to the exception processing
8 reference address ELADR (N) (where N = w2
w8) can be shown as follows. ELADR (w2) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 8 + 1 = ELADR (w1) +1 ... (Equation 16-2) ELADR (w3) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 8 + 2 = ELADR (w1) +2 ... (Equation 16-3) ELADR (w4) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 8 + 3 = ELADR (w1) +3 ... (Equation 16-4)

ELADR (w5) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 8 + 4 = ELADR (w1) +4 (Equation 16-5) ELADR (w6) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 8 + 5 = ELADR (w1) +5 (Equation 16-6) ELADR (w7) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 8 + 6 = ELADR (w1) +6 ...... (Equation 16-7) ELADR (w8) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 8 + 7 = ELADR (w1) +7 (Equation 16-8) Therefore, if stored in this way, the weight coefficient w1 All weighting coefficients W (w1 to w8) can be sequentially obtained only by incrementing seven times based on the reference address ELADR (w1).

Next, in the exception processing, "C, M, Y,
K ”component interpolation value IPL (N) (where N = C, M,
(Y, K) will be described. Reading unit 14
Assuming that the lower 4 bits of the color image data, that is, the lower 4 bits of the RGB signal, are (RL, GL, BL), the interpolation value IPL (N) of the “C, M, Y, K” component (where, N = C, M, Y, K), as in the above (Equation 5),
It can be shown as follows. IPL (N) = (w1 * f (HADR (A)) + w2 * f (HADR (B)) + w3 * f (HADR (C)) + w4 * f (HADR (D)) + w5 * f ( HADR (E)) + w6 * f (HADR (F)) + w7 * f (HADR (G)) + w8 * f (HADR (H))} / (16 * 16 * 16) ............ (Equation 17) )

Note that f (HADR) shown in (Equation 17)
(N)) (however, N = A to H) are obtained by incrementing “C, M,
This is grid point data of grid points “A to H” in the “Y, K” components.

Here, the weight coefficient W (w1 to w8) is
The lower 4 bits of the B signal, that is, (RL, GL,
BL), the above (Equation 8-1) to (Equation 14-
8), the interpolation value IPL (N) (where N = C, M,
(Equation 17) showing (Y, K) can be expressed as follows. [1] When RH = 15, GH <15, BH <15 IPL (N) = {(15-RL) * (16-GL) * (16-BL) * f (HADR (A)) + (15 -RL) * (16-GL) * BL * f (HADR (B)) + (15-RL) * GL * (16-BL) * f (HADR (C)) + (15-RL) * GL * BL * f (HADR (D)) + RL * (16-GL) * (16-BL) * f (HADR (E)) + RL * (16-GL) * BL * f (HADR (F)) + RL * GL * (16-BL) * f (HADR (G)) + RL * GL * BL * f (HADR (H))} / (15 * 16 * 16) ............ (Equation 18) Equation 18) can also be obtained by substituting “16 * RL / 15” for “RL” shown in Equation 7 above.

[2] When RH <15, GH = 15, BH <15 IPL (N) = {(16-RL) * (15-GL) * (16-BL) * f (HADR (A)) + (16-RL) * (15-GL) * BL * f (HADR (B)) + (16-RL) * GL * (16-BL) * f (HADR (C)) + (16-RL) * GL * BL * f (HADR (D)) + RL * (15-GL) * (16-BL) * f (HADR (E)) + RL * (15-GL) * BL * f (HADR (F )) + RL * GL * (16-BL) * f (HADR (G)) + RL * GL * BL * f (HADR (H))} / (16 * 15 * 16) ............ (Equation 19) (Equation 19) can also be obtained by substituting "16 * GL / 15" for "GL" shown in (Equation 7).

[3] When RH <15, GH <15, BH = 15 IPL (N) = {(16-RL) * (16-GL) * (15-BL) * f (HADR (A)) + (16-RL) * (16-GL) * BL * f (HADR (B)) + (16-RL) * GL * (15-BL) * f (HADR (C)) + (16-RL) * GL * BL * f (HADR (D)) + RL * (16-GL) * (15-BL) * f (HADR (E)) + RL * (16-GL) * BL * f (HADR (F )) + RL * GL * (15-BL) * f (HADR (G)) + RL * GL * BL * f (HADR (H))} / (16 * 16 * 15) ……… (Equation 20) (Equation 20) can also be obtained by substituting “16 * BL / 15” for “BL” shown in (Equation 7).

[4] When RH = 15, GH = 15, BH <15 IPL (N) = {(15-RL) * (15-GL) * (16-BL) * f (HADR (A)) + (15-RL) * (15-GL) * BL * f (HADR (B)) + (15-RL) * GL * (16-BL) * f (HADR (C)) + (15-RL) * GL * BL * f (HADR (D)) + RL * (15-GL) * (16-BL) * f (HADR (E)) + RL * (15-GL) * BL * f (HADR (F )) + RL * GL * (16-BL) * f (HADR (G)) + RL * GL * BL * f (HADR (H))} / (15 * 15 * 16) ……… (Equation 21) In addition, (Equation 21) uses “16 * RL / 15” for “RL” and “16 * GL / 1” for “GL” shown in (Equation 7).
5 "can be obtained.

[5] When RH <15, GH = 15, BH = 15 IPL (N) = {(16-RL) * (15-GL) * (15-BL) * f (HADR (A)) + (16-RL) * (15-GL) * BL * f (HADR (B)) + (16-RL) * GL * (15-BL) * f (HADR (C)) + (16-RL) * GL * BL * f (HADR (D)) + RL * (15-GL) * (15-BL) * f (HADR (E)) + RL * (15-GL) * BL * f (HADR (F )) + RL * GL * (15-BL) * f (HADR (G)) + RL * GL * BL * f (HADR (H))} / (16 * 15 * 15) ............ (Equation 22) In addition, (Equation 22) uses “16 * GL / 15” for “GL” and “16 * BL / 1” for “BL” shown in (Equation 7).
5 "can be obtained.

[6] When RH = 15, GH <15, BH = 15 IPL (N) = {(15-RL) * (16-GL) * (15-BL) * f (HADR (A)) + (15-RL) * (16-GL) * BL * f (HADR (B)) + (15-RL) * GL * (15-BL) * f (HADR (C)) + (15-RL) * GL * BL * f (HADR (D)) + RL * (16-GL) * (15-BL) * f (HADR (E)) + RL * (16-GL) * BL * f (HADR (F )) + RL * GL * (15-BL) * f (HADR (G)) + RL * GL * BL * f (HADR (H))} / (15 * 16 * 15) ……… (Equation 23) (Equation 23) is obtained by adding “16” to “RL” shown in (Equation 7).
* RL / 15 "can also be obtained by substituting" 16 * BL / 15 "for" BL ".

[7] When RH = 15, GH = 15, BH = 15 IPL (N) = {(15-RL) * (15-GL) * (15-BL) * f (HADR (A)) + (15-RL) * (15-GL) * BL * f (HADR (B)) + (15-RL) * GL * (15-BL) * f (HADR (C)) + (15-RL) * GL * BL * f (HADR (D)) + RL * (15-GL) * (15-BL) * f (HADR (E)) + RL * (15-GL) * BL * f (HADR (F )) + RL * GL * (15-BL) * f (HADR (G)) + RL * GL * BL * f (HADR (H))} / (15 * 15 * 15) ............ (Equation 24) In addition, (Equation 24) indicates that “16 * RL / 15” is used for “RL” and “16 * GL / 1” is used for “GL” shown in (Equation 7).
"5" can also be obtained by substituting "16 * BL / 15" for "BL".

Further, f shown in (Equation 18) to (Equation 24)
(HADR (N)) (where N = A to H) is based on the above (Equation 2-1), and is based on the grid points “A to H” in the “C, M, Y, K” components obtained by the increment. This is grid point data. Therefore, as shown in the LUT of the weight coefficient including the case corresponding to the exception processing in FIG.
According to the “seven ways” exception processing shown in [7], “RL,
"GL, BL" respectively "16 * RL / 15, 16 * G
L / 15, 16 * BL / 15 "
When (w1 to w8) are stored, (Equation 18) to (Equation 2)
Without performing the operation of 4), “C,
M, Y, K ”component interpolation value IPL (N) (where N =
C, M, Y, K).

Next, in the facsimile machine 1, when the reading unit 14 outputs the RGB signal of the conversion point P,
The operation of the color conversion process for pixels will be described with reference to the flowchart shown in FIG. Note that this operation is performed by the RO
The program is executed under the control of the MPU 11 based on the program stored in the M12.

In step S1 shown in FIG. 11, the lower 4 bits, ie, (RL, GL, BL), are extracted from the RGB signals at the conversion point P. In step S2, (RL,
GL, BL), the reference address LADR (w1) of the weight coefficient w1 is calculated. Specifically, based on the above (Equation 4-1), the reference address LA of the weight coefficient w1
DR (w1) is calculated.

In step S3, the weighting factors W (w1 to w8) in the cube surrounding the transformation point P are stored in the ROM.
12 are sequentially read. Specifically, the reference address L of the weight coefficient w1 calculated in step S2
The weight coefficients W (w1 to w8) are sequentially incremented from the ADR (w1), and are sequentially read from the LUT of the weight coefficients W (w1 to w8) shown in FIG. Note that, instead of the processing in steps S2 and S3, the weighting coefficients W (w1 to w8) may be calculated based on (RL, GL, BL) extracted in step S1. Specifically, the weighting factors W (w1 to w8) may be calculated based on the above (Equation 6-1) to (Equation 6-8).

In step S4, the RG of the conversion point P
The upper 4 bits from the B signal, that is, (RH, G
H, BH) are extracted. In step S5, (RH, GH, B
Based on H), the reference address HADR (A) of the grid point “A” in the “C” component is calculated. In particular,
Based on (Equation 2-1), the reference address HADR (A) of the grid point “A” in the “C” component is calculated.

In step S 6, the grid point data of the grid points “A to H” in the cube surrounding the conversion point P are sequentially read from the ROM 12. Specifically, the grid points “A to H” in the “C” component are sequentially incremented from the reference address HADR (A) of the grid point “A” in the “C” component calculated in step S5.
Is the LU of the grid point data shown in FIG.
It is sequentially read from T.

In step S7, an interpolation operation at the conversion point P is performed. Specifically, step S3
Based on the weighting factors W (w1 to w8) read in step S6 and the grid point data of the grid points “A to H” in the “C” component read in step S6, , An interpolation operation at the conversion point P is performed.

In step S8, it is determined whether there is a next component. Specifically, the interpolation operation of the “M” component is performed when the interpolation operation of the “C” component is performed, and the interpolation operation of the “Y” component and the “Y” component is performed when the interpolation operation of the “M” component is performed. In this case, it is determined whether or not there is a “K” component. If there is a next component, the process proceeds to step S9. On the other hand, when there is no next component, that is, all “C, M,
When the interpolation calculation is completed for the “Y, K” components,
This processing ends.

In step S9, the reference address of the grid point "A" in the next component is calculated. More specifically, as shown in FIG. 5, since the grid point data of the grid points “A to H” is stored for the “C, M, Y, K” components, the calculation is performed in step S5. Done "C"
Address HADR of grid point "A" in the component
Only (A) is sequentially incremented. And
Steps S6 to S9 are repeatedly executed, and the interpolation calculation of “M, Y, K” at the conversion point P is performed.
That is, Steps S6 to S9 are repeatedly executed, the interpolation calculation of the “C, M, Y, K” components at the conversion point P is performed, and the RGB signals at the conversion point P are converted into CMYK signals. In general, since there are a large number of pixels to be converted, this process is repeatedly performed on all the read pixels.

As described above, according to the first embodiment, the following operations and effects can be obtained. (1) As shown in FIG. 5, the “C, M, Y, K” components of (RH, GH, BH) are arranged in the order of “C, M, Y, K”.
Grid point data is stored in the ROM 12 in the order of grid points "A to H" for the "K" component. In other words, the grid point data of the grid points “A to H” in the cube are continuously stored. For this reason, if the reference address HADR (A) of the grid point “A” in the cube surrounding the conversion point P is known based on the above (Equation 2-1), the other grid points “B to H” can be simply incremented sequentially. Can be obtained. As a result, the grid point “A” in the cube
ＨH ”can be obtained quickly.

As shown in FIG. 7, (RL, GL,
BL) in the order of w1 to w8,
12 is stored. Therefore, based on the above (Equation 4-1), the reference address LADR (w1) of the weight coefficient w1
, Other weighting factors w2 to w8 can be obtained only by sequentially incrementing. As a result, the weight coefficient W (w1 to w8) can also be obtained quickly. Therefore, when performing color conversion processing from RGB signals to CMYK signals, color conversion processing can be performed at high speed even by using software.

(2) Since the color conversion processing is performed using software, a dedicated LSI is not required. Moreover, since it is not configured using hardware, LSI
It is possible to easily reduce the size and cost of the device. In addition, since a dedicated circuit is not required, various interpolation calculation methods can be supported.

(3) In the flowchart shown in FIG. 11, first, the weight coefficients W (w1 to w8) are read.
This is because the weight coefficients W (w1 to w8) are “C, M, Y,
This is because it is the same regardless of the “K” component. Therefore, the interpolation calculation processing can be performed quickly. Therefore, the color conversion processing can be performed at high speed.

(4) As is apparent from the above (Equation 5), the product-sum operation is performed eight times in the interpolation operation process. However, some MPUs process instructions for repeatedly performing a product-sum operation at a higher speed.
Therefore, if an MPU having an instruction to repeatedly perform a product-sum operation is used, color conversion processing can be performed at high speed.

(5) In the first embodiment, even when the conversion point P corresponds to the exception processing, the color conversion processing is performed using the usual weight coefficient W. For this reason, when the conversion point P corresponds to the exception processing, the value after the color conversion processing includes some error. However, it is extremely rare that the conversion point P corresponds to exception processing. Therefore, the color conversion processing can be further speeded up. Moreover, since the conversion point P rarely corresponds to the exception processing, the error does not greatly affect the entire image on which the color conversion processing is performed.

[Second Embodiment] Case of Cube Interpolation (8-Point Interpolation) In the second embodiment, the same configuration as the first embodiment is the same as that of the first embodiment. The description is omitted by attaching reference numerals. In the second embodiment, a case corresponding to exception processing in the first embodiment is considered. Therefore, in the second embodiment, the ROM 12 stores the LUT of the grid point data shown in FIG.
The LUT for determining whether the conversion point P shown in FIG. 9 corresponds to the exception processing and the LUT of the weight coefficient W (w1 to w8) including the case corresponding to the exception processing shown in FIG. 10 are stored.

Next, in the facsimile machine 1, when the reading unit 14 outputs the RGB signal of the conversion point P,
FIGS. 12 and 13 show the operation of the color conversion processing for the pixels.
This will be described with reference to the flowchart shown in FIG. This operation is performed based on a program stored in the ROM 12 based on M
It is executed under the control of the PU 11.

In step S11 shown in FIG.
The upper 4 bits, that is, (RH, GH, BH) are extracted from the RGB signal at the conversion point P. Step S12
In, it is determined based on (RH, GH, BH) extracted in step S11 whether or not the conversion point P corresponds to exception processing. Specifically, the reference address ZHADR (Z) of “Z” indicating whether or not the exception processing is performed is calculated based on the above (Equation 15).
Then, the value of “Z” is extracted based on the reference address ZHADR (Z). Specifically, whether or not the conversion point P corresponds to the exception processing is determined based on the LUT for determining whether or not the conversion point P corresponds to the exception processing. That is, when the value of “Z” indicating whether or not the exception processing is performed is “1 to 7”, it is determined that the processing corresponds to the exception processing, and the process proceeds to step S31 illustrated in FIG. On the other hand, when the value of “Z” indicating whether or not the exception processing is performed is “0”, it is determined that the processing does not correspond to the exception processing, and
Move to step S13. Note that the above (Equation 15-1)
May be determined on the basis of the exception processing.

In step S13, the R of the conversion point P
The lower 4 bits from the GB signal, that is, (RL, G
L, BL) are extracted. In step S14,
(RL, GL,
BL), the reference address ELADR (w1) of the weight coefficient w1 including the case corresponding to the exception processing is calculated. Specifically, the reference address ELADR (w1) of the weight coefficient w1 is calculated based on the above (Equation 16-1).

In step S15, the weight coefficient W (w1 to w8) in the cube surrounding the transformation point P
They are sequentially read from M12. Specifically, the weight coefficient w1 calculated in step S14 is sequentially incremented from the reference address ELADR (w1),
All the weighting factors W (w1 to w8) include the weighting factors W (w1 to w8) including the case where the exception processing shown in FIG.
8) are sequentially read from the LUT. More specifically,
In the LUT of the weight coefficient W (w1 to w8) including the case corresponding to the exception processing shown in FIG. 10, “Z (=) calculated based on the (Equation 15) in the processing of step S12 shown in FIG. 0) ", a weighting coefficient W corresponding to the value of"
(W1 to w8) are sequentially read.

It should be noted that, instead of the processing in steps S14 and S15, the (R
L, GL, BL) based on the weighting factors W (w1 to w
8) may be calculated. Specifically, the above (Equation 6-1)
Based on (Equation 6-8), weighting factors W (w1 to w8)
May be calculated.

In step S16, the conversion point P
The upper 4 bits from the GB signal, that is, (RH, G
H, BH) are extracted. Note that the upper 4 bits
Is the same processing as in step S11, so the top 4 [b] extracted in step S11
it] may be used as it is.

In step S17, the reference address HADR (A) of the grid point "A" in the "C" component is calculated based on (RH, GH, BH) extracted in step S16. Specifically, the above (Equation 2)
Based on -1), the reference address HADR (A) of the grid point “A” in the “C” component is calculated.

The reference address HADR (A) of the grid point “A” in the “C” component is the reference address ZHADR of “Z” calculated in step S12.
(Z), that is, a reference address ZHADR of “Z” indicating whether or not the exception processing shown in (Equation 15) is applicable.
(Z) may be multiplied by “32” to calculate the reference address HADR (A) of the grid point “A” in the “C” component.

In step S 18, the grid point data of the grid points “A to H” in the cube surrounding the conversion point P are sequentially read from the ROM 12. Specifically, the grid point “A” is incremented sequentially from the reference address HADR (A) of the grid point “A” in the “C” component calculated in step S17.
The grid point data “H” is sequentially read from the grid point data LUT shown in FIG.

In step S19, an interpolation operation at the conversion point P is performed. Specifically, the step S
Weighting coefficient W (w1 to w8) read out at 15
Based on the grid point data of the grid points “A to H” of the “C” component read in step S18, the interpolation calculation at the conversion point P is performed by (Equation 5).

In step S20, it is determined whether there is a next component. Specifically, the interpolation operation of the “M” component is performed when the interpolation operation of the “C” component is performed, and the interpolation operation of the “Y” component and the “Y” component is performed when the interpolation operation of the “M” component is performed. In this case, it is determined whether or not there is a “K” component.
If there is a next component, the process proceeds to step S21. On the other hand, when there is no next component, that is, when all “C,
When the interpolation calculation has been completed for the "M, Y, K" components, this processing ends.

In step S21, the reference address of the grid point "A" in the next component is calculated. More specifically, as shown in FIG. 5, since the grid point data of the grid points “A to H” is stored for the “C, M, Y, K” components, the calculation is performed in step S7. Done "C"
Address HADR of grid point "A" in the component
Only (A) is sequentially incremented. And
Steps S <b> 18 to S <b> 21 are repeatedly executed, and the interpolation calculation of “M, Y, K” at the conversion point P is performed. That is, steps S18 to S21 are repeatedly executed, and “C, M, Y,
The interpolation operation of the “K” component is performed, and the RGB signals at the conversion point P are converted into CMYK signals.

In step S31 shown in FIG.
The lower 4 bits, that is, (RL, GL, BL), are extracted from the RGB signal at the conversion point P. Step S32
In, based on the (RL, GL, BL) extracted in step S31, the reference address ELADR (w
1) is calculated. Specifically, based on (Equation 16-1), the reference address ELADR (w
1) is calculated.

In step S33, the weight coefficient W (w1 to w8) in the cube surrounding the transformation point P
They are sequentially read from M12. Specifically, the weight coefficient w1 calculated in step S32 is sequentially incremented from the reference address ELADR (w1),
All the weighting factors W (w1 to w8) include the weighting factors W (w1 to w8) including the case where the exception processing shown in FIG.
8) are sequentially read from the LUT. More specifically,
In the LUT of the weight coefficient W (w1 to w8) including the case corresponding to the exception processing shown in FIG. 10, “Z (=) calculated based on the (Equation 15) in the processing of step S12 shown in FIG. 1 to 7) "are sequentially read out.

Instead of the processing of steps S32 and S33, a value "Z" indicating whether or not the exception processing calculated in the processing of step S12 shown in FIG.
, The weighting coefficient W (w1 to w8) may be calculated. Specifically, according to the case where the value “Z” indicating whether or not the exception processing is applicable is “1 to 7”, in other words, (R
H, GH, BH) according to (Equations 8-1 to 8) to
The weighting factors W (w1 to w8) in the case of exception processing may be calculated by (Equations 14-1 to 8).

In step S34, R of conversion point P
The upper 4 bits from the GB signal, that is, (RH, G
H, BH) are extracted. Note that the upper 4 bits
Is the same as step S11 shown in FIG. 12, and the upper 4 bits extracted in step S11 shown in FIG. 12 may be used as it is.

In step S35, the reference address HADR (A) of the grid point "A" in the "C" component is calculated based on (RH, GH, BH) extracted in step S34. Specifically, the above (Equation 2)
Based on -1), the reference address HADR (A) of the grid point “A” in the “C” component is calculated.

The reference address HADR (A) of the grid point “A” in the “C” component is the reference address ZHADR of “Z” calculated in step S12.
(Z), that is, a reference address ZHADR of “Z” indicating whether or not the exception processing shown in (Equation 15) is applicable.
(Z) may be multiplied by “32” to calculate the reference address HADR (A) of the grid point “A” in the “C” component.

In step S 36, the grid point data of the grid points “A to H” in the cube surrounding the conversion point P are sequentially read from the ROM 12. Specifically, the grid point “A” of the “C” component is sequentially incremented from the reference address HADR (A) of the grid point “A” in the “C” component calculated in step S35.
The grid point data “H” is sequentially read from the grid point data LUT shown in FIG.

In step S37, an interpolation operation at the conversion point P is performed. Specifically, the step S
Weighting coefficient W (w1 to w8) read out at 33
Based on the grid point data of the grid points “A to H” in the “C” component read in step S36, the interpolation calculation at the conversion point P is performed by (Equation 5).

In step S38, it is determined whether there is a next component. Specifically, the interpolation operation of the “M” component is performed when the interpolation operation of the “C” component is performed, and the interpolation operation of the “Y” component and the “Y” component is performed when the interpolation operation of the “M” component is performed. In this case, it is determined whether or not there is a “K” component.
If there is a next component, the process proceeds to step S39. On the other hand, when there is no next component, that is, when all “C,
When the interpolation calculation has been completed for the "M, Y, K" components, this processing ends.

In step S39, the reference address of grid point "A" in the next component is calculated. Specifically, as shown in FIG. 5, since the grid point data of the grid points “A to H” is stored for the “C, M, Y, K” components, the calculation is performed in the step S35. Address HAD of the grid point "A" in the calculated "C" component
It simply increments R (A) sequentially. Then, steps S36 to S39 are repeatedly executed, and the interpolation calculation of “M, Y, K” at the conversion point P is performed. That is, steps S36 to S39 are repeatedly executed, and “C, M, Y,
The interpolation operation of the “K” component is performed, and the RGB signals at the conversion point P are converted into CMYK signals. In general, since there are a large number of pixels to be converted, this process is repeatedly performed on all the read pixels.

As described in detail above, according to the second embodiment, the following operation and effect can be obtained in addition to the operation and effect of the first embodiment. (1) In the second embodiment, as shown in FIG. 10, the weight coefficient W including the case corresponding to the exceptional processing is w1
Ｗw8 are stored in the ROM 12 in this order. For this reason, based on the above (Equation 16-1), the reference address ELADR of the weight coefficient w1 including the case corresponding to the exception processing
Once (w1) is known, it is only necessary to increment sequentially,
Weighting factors w2 to w8 can also be obtained. Therefore, even when the conversion point P corresponds to the exception processing, the color conversion processing can be performed at high speed using software. Moreover, even when the conversion point P corresponds to exception processing,
The color conversion process can be performed without including an error.

(2) When judging whether or not the process corresponds to the exception processing, the judgment is not made based on whether or not each value of (RH, GH, BH) is “15”. The value of “Z” indicating whether or not the above applies, that is, the above (Equation 1)
The decision is made based on 5). For this reason, (RH,
GH, BH) can increase the processing speed of the entire apparatus as compared with the processing of determining whether any of the values is “15”. Moreover, according to the value of “Z”,
It is possible to determine which of the exception processes corresponds. Therefore, even when the conversion point P corresponds to the exception processing, the color conversion processing can be performed at higher speed.

[Third Embodiment] Case of Cube Interpolation (8-Point Interpolation) In the third embodiment, the same configuration as the first embodiment is the same as that of the first embodiment. The description is omitted by attaching reference numerals. In the third embodiment, as in the second embodiment, a case corresponding to exception processing in the first embodiment is considered. In addition, the third embodiment is different from the second embodiment in that the color conversion process is executed without determining whether or not the process corresponds to the exception process.

In the third embodiment, the ROM 12
Is an LUT for grid point data shown in FIG. 5, and an LU for judging whether the conversion point P shown in FIG. 9 corresponds to exception processing.
T and the LUT of the weighting coefficient W (w1 to w8) including the case corresponding to the exception processing shown in FIG. 10 are stored.

Next, in the facsimile machine 1, when the RGB signal of the conversion point P is output from the reading unit 14,
The operation of the color conversion process for pixels will be described with reference to the flowchart shown in FIG. Note that this operation is performed by the RO
The program is executed under the control of the MPU 11 based on the program stored in the M12.

In step S41 shown in FIG.
The upper 4 bits, that is, (RH, GH, BH) are extracted from the RGB signal at the conversion point P. Step S42
In, based on (RH, GH, BH) extracted in step S41, a reference address ZHADR (Z) of “Z” indicating whether or not an exception process is applicable is calculated. Specifically, based on the above (Equation 15), the reference address Z of “Z” indicating whether or not the exception processing is performed.
HADR (Z) is calculated.

In step S43, reference address ZHA of "Z" calculated in step S42.
The value of “Z” is extracted based on DR (Z). Specifically, the value of “Z” is extracted based on the LUT for determining whether the conversion point P shown in FIG. 9 corresponds to exception processing. Therefore, when the value of “Z” is “0”,
It can be determined that the conversion point P does not correspond to exception processing. When the value of “Z” is “1 to 7”, it can be determined that the conversion point P corresponds to exception processing,
It is possible to determine which of the seven exceptions [1] to [7] corresponds to the exception processing.

In step S44, R of conversion point P
The lower 4 bits from the GB signal, that is, (RL, G
L, BL) are extracted. In step S45,
(RL, GL,
BL), the reference address ELADR (w1) of the weight coefficient w1 including the case corresponding to the exception processing is calculated. Specifically, the reference address ELADR (w1) of the weight coefficient w1 is calculated based on the above (Equation 16-1).

In step S46, the weighting factors W (w1 to w8) in the cube surrounding the transformation point P are set to RO
They are sequentially read from M12. Specifically, the weight coefficient w1 calculated in step S45 is sequentially incremented from the reference address ELADR (w1),
All the weighting factors W (w1 to w8) include the weighting factors W (w1 to w8) including the case where the exception processing shown in FIG.
8) are sequentially read from the LUT. More specifically,
In the weight coefficient W (w1 to w8) including the case corresponding to the exception processing shown in FIG. 10, the weight coefficient W corresponding to “Z (= 0 to 7)” extracted in step S43.
(W1 to w8) are read.

In step S47, R of conversion point P
The upper 4 bits from the GB signal, that is, (RH, G
H, BH) are extracted. Note that the upper 4 bits
Is the same processing as in step S41, so the top 4 [b] extracted in step S41
it] may be used as it is.

In step S48, the reference address HADR (A) of the grid point "A" in the "C" component is calculated based on (RH, GH, BH) extracted in step S47. Specifically, the above (Equation 2)
Based on -1), the reference address HADR (A) of the grid point “A” in the “C” component is calculated.

The reference address HADR (A) of the grid point “A” in the “C” component is the reference address ZHADR of “Z” calculated in step S42.
(Z), that is, a reference address ZHADR of “Z” indicating whether or not the exception processing shown in (Equation 15) is applicable.
(Z) may be multiplied by “32” to calculate the reference address HADR (A) of the grid point “A” in the “C” component.

In step S 49, the grid point data of the grid points “A to H” in the cube surrounding the conversion point P are sequentially read from the ROM 12. Specifically, the grid point “A” is incremented sequentially from the reference address HADR (A) of the grid point “A” in the “C” component calculated in step S48.
H "is the grid point data" A to H "shown in FIG.
Are sequentially read from the LUT of the lattice point data.

In step S50, an interpolation operation at the conversion point P is performed. Specifically, the step S
Weight coefficient W (w1 to w8) read out at 46
Based on the above and the grid point data of the grid points “A to H” in the “C” component read in step S49, the interpolation calculation at the conversion point P is performed by (Equation 5).

In step S51, it is determined whether there is a next component. Specifically, the interpolation operation of the “M” component is performed when the interpolation operation of the “C” component is performed, and the interpolation operation of the “Y” component and the “Y” component is performed when the interpolation operation of the “M” component is performed. In this case, it is determined whether or not there is a “K” component.
If there is a next component, the process proceeds to step S52. On the other hand, when there is no next component, that is, when all “C,
When the interpolation calculation has been completed for the "M, Y, K" components, this processing ends.

In step S52, the reference address of the grid point "A" in the next component is calculated. Specifically, as shown in FIG. 5, since the grid point data of the grid points “A to H” is stored for the “C, M, Y, K” components, the calculation is performed in the step S48. Address HAD of the grid point "A" in the calculated "C" component
It simply increments R (A) sequentially. Then, steps S49 to S52 are repeatedly executed, and the interpolation calculation of “M, Y, K” at the conversion point P is performed. That is, steps S49 to S52 are repeatedly executed, and “C, M, Y,
The interpolation operation of the “K” component is performed, and the RGB signals at the conversion point P are converted into CMYK signals. In general, since there are a large number of pixels to be converted, this process is repeatedly performed on all the read pixels.

As described above in detail, according to the third embodiment, the following operation and effect can be obtained in addition to the operation and effect of the second embodiment. (1) The interpolation calculation is performed without determining whether the conversion point P corresponds to the exception processing. Therefore, unlike the second embodiment (the flowcharts shown in FIGS. 12 and 13), the same processing (the flowchart shown in FIG. 14) is performed regardless of whether the conversion point P corresponds to the exception processing. Color conversion processing can be performed. Therefore, even when the color conversion processing is performed by software, the processing can be performed at a higher speed. Moreover, even when the color conversion processing is configured by hardware, the color conversion processing can be performed by the same processing, so that a simpler configuration can be achieved.

[Fourth Embodiment] Case of Triangular Pyramid Interpolation (Four-Point Interpolation) Next, a fourth embodiment in which the present invention is embodied in a facsimile apparatus will be described with reference to the drawings. In the fourth embodiment, the same components as those in the first embodiment are denoted by the same reference numerals as in the first embodiment, and the description is omitted.

In the fourth embodiment, the ROM 1
2 has different LUT data. That is, data necessary for triangular pyramid interpolation (four-point interpolation) obtained by dividing a cube into six is stored. Specifically, an LUT of weighting coefficients W (w1 to w4) shown in FIG.
L, GL, and BL) indicating the offset determined by the magnitude relationship between the values and the LU of the grid point data shown in FIG.
Store T.

Next, the principle of triangular pyramid interpolation (four-point interpolation) will be described with reference to the drawings. As shown in FIG. 15 (a), in the RGB space, each lower 4 [bi] of the RGB signal
t] is (RL, GL, BL), and the cube is expressed as “RL = G
“L plane”, “GL = BL plane” and “BL = RL plane”
, The cube becomes 6 as shown in FIG.
Divided into three triangular pyramids.

As shown in FIG. 16, when the cube is divided into six triangular pyramids, based on the magnitude relation of each value of (RL, GL, BL), the transformation point P It can be determined whether or not there is a triangular pyramid.

That is, FIG. 16A shows BL>GL> R
16B shows the case of GL>RL> BL, FIG. 16C shows the case of RL>BL> GL, and FIG.
FIG. 16D shows the case where GL ≧ BL ≧ RL (where RL ≠ GL), and FIG. 16E shows the case where RL ≧ GL ≧ BL.
(F) shows the case where BL ≧ RL ≧ GL (where GL ≠ BL). FIG. 16D shows GL =
FIG. 16E includes the planes BL and BL = RL, and FIG.
FIG. 16F includes the planes of GL and GL = BL and the line of RL = GL = BL, and FIG. 16F includes the planes of BL = RL and RL = GL.

Here, FIGS. 16A to 16F are in contact with the other two surfaces of the other triangular pyramid. Therefore, the calculation result is the same regardless of which triangular pyramid includes the boundary surface. Therefore,
In the present embodiment, these boundary surfaces and boundaries are shown in FIG.
It is described as being included in (d) to (f). In addition, it is also possible to think that it is included in FIGS.

In addition, the weight coefficients W (w1 to w4) are calculated based on the magnitude relation between the values of (RL, GL, BL). That is, when “LL, LM, LS” are set in the descending order of the values of (RL, GL, BL), the weighting factors W (w1 to w1)
w4) can be shown as follows. w1 = 16-LL (Equation 30-1) w2 = LL-LM (Equation 30-2) w3 = LM-LS (Equation 30-3) w4 = LS (Equation 30-3) 30-4)

Therefore, the weighting factors W (w1 to w4) in the cases of FIGS. 16A to 16F are calculated. [A] Weight coefficient W in the case of BL>GL> RL shown in FIG. 16 (a) FIG. 17 shows a triangle in the case of FIG. 16 (a), that is, the case where the conversion point P is BL>GL> RL. The cone is shown.

As shown in FIGS. 18 (a) to (d), the triangular pyramid shown in FIG. 17 is further divided into four triangular pyramids based on the conversion point P, and the volumes Va to Vd
Is calculated. First, the volume V of the triangular pyramid shown in FIG.
a can be shown as follows. Va = 1/3 * (16 * 16) / 2 * (16-BL) = 1/6 * 16 * 16 * (16-BL) ............ (Equation 35-1)

Next, the triangular pyramid shown in FIG.
This is shown in FIG. When the triangular pyramid shown in FIG. 19A is viewed from above, it can be seen as shown in FIG. 19B. Therefore, the volume Vc of the triangular pyramid shown in FIG.
Can be shown as follows. Vc = 1/3 * (16 * 16 * SQRT (2)) / 2 * (GL-RL) / SQRT (2) = 1/6 * 16 * 16 * (GL-RL) ............ (Equation 35- 2) “SQRT” indicates a square root. same as below.

Next, the volume V of the triangular pyramid shown in FIG.
d can be expressed as follows. Vd = 1/3 * (16 * 16) / 2 * RL = 1/6 * 16 * 16 * RL ............ (Equation 35-3)

From the above (Equation 35-1) to (Equation 35-3), the volume Vb of the triangular pyramid shown in FIG. 18B can be expressed as follows. Vb = Overall product-(Va + Vc + Vd) = 1/6 * 16 * 16 * {16- (16-BL)-(GL-RL) -RL} = 1/6 * 16 * 16 * (BL- GL) ... (Equation 35-4)

As a result, the ratio of the volumes Va to Vd of the triangular pyramids shown in FIGS. 18A to 18D can be expressed as follows. Va: Vb: Vc: Vd = 16-BL: BL-GL: GL-RL: RL (Equation 35-5) Therefore, the lower 4 bits of the RGB signal, that is, (R
L, GL, BL) by volume ratio Va: Vb: Vc:
Vd is the weight coefficient W in the triangular pyramid.

Therefore, according to the relationship of BL>GL> RL and (Equation 30-1) to (Equation 30-4), the weight coefficient W
(W1 to w4) can be shown as follows. w1: w2: w3: w4 = 16-BL: BL-GL: GL-RL: RL (Equation 35-6)

[B] GL> RL shown in FIG. 16B
Weight coefficient W in case of> BL FIG. 20 shows a triangular pyramid in the case of FIG. 16B, that is, in the case where the conversion point P is GL>RL> BL.

As shown in FIGS. 21 (a) to 21 (d), the triangular pyramid shown in FIG. 20 is further divided into four triangular pyramids based on the transformation point P, and the volumes Va to Vd
Is calculated. First, the volume V of the triangular pyramid shown in FIG.
a can be shown as follows. Va = 1/3 * (16 * 16) / 2 * (16-GL) = 1/6 * 16 * 16 * (16-GL) ............ (Equation 36-1)

Next, the triangular pyramid shown in FIG.
This is shown in FIG. When the triangular pyramid shown in FIG. 22A is viewed from the near side, it can be shown as shown in FIG. 22B. Therefore, the volume Vc of the triangular pyramid shown in FIG.
Can be shown as follows. Vc = 1/3 * (16 * 16 * SQRT (2)) / 2 * (RL-BL) / SQRT (2) = 1/6 * 16 * 16 * (RL-BL) ............ (Equation 36− 2)

Next, the volume V of the triangular pyramid shown in FIG.
d can be expressed as follows. Vd = 1/3 * (16 * 16) / 2 * BL = 1/6 * 16 * 16 * BL ............ (Equation 36-3)

From the above (Equation 36-1) to (Equation 36-3), the volume Vb of the triangular pyramid shown in FIG. 21B can be expressed as follows. Vb = Overall product-(Va + Vc + Vd) = 1/6 * 16 * 16 * {16- (16-GL)-(RL-BL) -BL} = 1/6 * 16 * 16 * (GL- RL) ... (Equation 36-4)

As a result, the ratio of the volumes Va to Vd of the triangular pyramids shown in FIGS. 21A to 21D can be expressed as follows. Va: Vb: Vc: Vd = 16-GL: GL-RL: RL-BL: BL (Equation 36-5) Therefore, the lower 4 bits of the RGB signal, that is, (R
L, GL, BL) by volume ratio Va: Vb: Vc:
Vd is the weight coefficient W in the triangular pyramid.

Therefore, according to the relationship of GL>RL> BL and the above (Equation 30-1) to (Equation 30-4), the weight coefficient W
(W1 to w4) can be shown as follows. w1: w2: w3: w4 = 16-GL: GL-RL: RL-BL: BL (Equation 36-6)

[C] RL> BL shown in FIG. 16 (c)
Weight coefficient W in case of> GL FIG. 23 shows a triangular pyramid in the case of FIG. 16C, that is, in the case where the transformation point P is RL>BL> GL.

As shown in FIGS. 24 (a) to 24 (d), the triangular pyramid shown in FIG. 23 is further divided into four triangular pyramids based on the conversion point P, and the volumes Va to Vd
Is calculated. First, the volume V of the triangular pyramid shown in FIG.
a can be shown as follows. Va = 1/3 * (16 * 16) / 2 * (16-RL) = 1/6 * 16 * 16 * (16-RL) ............ (Equation 37-1)

Next, the triangular pyramid shown in FIG.
This is shown in FIG. When the triangular pyramid shown in FIG. 25A is viewed from the right, it can be shown as in FIG. 25B. Therefore, the volume Vc of the triangular pyramid shown in FIG.
Can be shown as follows. Vc = 1/3 * (16 * 16 * SQRT (2)) / 2 * (BL-GL) / SQRT (2) = 1/6 * 16 * 16 * (BL-GL) ............ (Equation 37- 2)

Next, the volume V of the triangular pyramid shown in FIG.
d can be expressed as follows. Vd = 1/3 * (16 * 16) / 2 * GL = 1/6 * 16 * 16 * GL ... (Equation 37-3)

From the above (Equation 37-1) to (Equation 37-3), the volume Vb of the triangular pyramid shown in FIG. 24B can be expressed as follows. Vb = Overall product- (Va + Vc + Vd) = 1/6 * 16 * 16 * {16- (16-RL)-(BL-GL) -GL} = 1/6 * 16 * 16 * (RL- BL) ............ (Equation 37-4)

As a result, the ratio of the volumes Va to Vd of the triangular pyramids shown in FIGS. 24A to 24D can be expressed as follows. Va: Vb: Vc: Vd = 16-RL: RL-BL: BL-GL: GL (Expression 37-5) Therefore, the lower 4 bits of the RGB signal, that is, (R
L, GL, BL) by volume ratio Va: Vb: Vc:
Vd is the weight coefficient W in the triangular pyramid.

Therefore, according to the relationship of RL>BL> GL and (Equation 30-1) to (Equation 30-4), the weight coefficient W
(W1 to w4) can be shown as follows. w1: w2: w3: w4 = 16-RL: RL-BL: BL-GL: GL (Equation 37-6)

[D] GL ≧ BL shown in FIG.
Weight coefficient W in the case of ≧ RL (where RL ≠ GL) FIG. 26 shows a triangular pyramid in the case of FIG. 16D, that is, in the case where the conversion point P is GL ≧ BL ≧ RL.

As shown in FIGS. 27 (a) to (d), the triangular pyramid shown in FIG. 26 is further divided into four triangular pyramids based on the transformation point P, and the volumes Va to Vd
Is calculated. First, the volume V of the triangular pyramid shown in FIG.
a can be shown as follows. Va = 1/3 * (16 * 16) / 2 * (16-GL) = 1/6 * 16 * 16 * (16-GL) ............ (Equation 38-1)

Next, the triangular pyramid shown in FIG.
This is shown in FIG. When the triangular pyramid shown in FIG. 28A is viewed from the near side, it can be shown as shown in FIG. Therefore, the volume Vc of the triangular pyramid shown in FIG.
Can be shown as follows. Vc = 1/3 * (16 * 16 * SQRT (2)) / 2 * (BL-RL) / SQRT (2) = 1/6 * 16 * 16 * (BL-RL) ............ (Equation 38- 2)

Next, the volume V of the triangular pyramid shown in FIG.
d can be expressed as follows. Vd = 1/3 * (16 * 16) / 2 * RL = 1/6 * 16 * 16 * RL ............ (Equation 38-3)

From Equations 38-1 to 38-3, the volume Vb of the triangular pyramid shown in FIG. 27B can be expressed as follows. Vb = Overall product-(Va + Vc + Vd) = 1/6 * 16 * 16 * {16- (16-GL)-(BL-RL) -RL} = 1/6 * 16 * 16 * (GL- BL) ... (Equation 38-4)

As a result, the ratio of the volumes Va to Vd of the triangular pyramids shown in FIGS. 27A to 27D can be expressed as follows. Va: Vb: Vc: Vd = 16-GL: GL-BL: BL-RL: RL (Equation 38-5) Therefore, the lower 4 bits of the RGB signal, that is, (R
L, GL, BL) by volume ratio Va: Vb: Vc:
Vd is the weight coefficient W in the triangular pyramid.

Therefore, according to the relationship of GL ≧ BL ≧ RL and (Equation 30-1) to (Equation 30-4), the weight coefficient W
(W1 to w4) can be shown as follows. w1: w2: w3: w4 = 16-GL: GL-BL: BL-RL: RL (Equation 38-6)

[E] RL ≧ GL shown in FIG.
Weighting coefficient W in case of ≧ BL FIG. 29 shows a triangular pyramid in the case of FIG. 16E, that is, in the case where the conversion point P satisfies RL ≧ GL ≧ BL.

As shown in FIGS. 30 (a) to 30 (d), the triangular pyramid shown in FIG. 29 is further divided into four triangular pyramids based on the transformation point P, and the volumes Va to Vd
Is calculated. First, the volume V of the triangular pyramid shown in FIG.
a can be shown as follows. Va = 1/3 * (16 * 16) / 2 * (16-RL) = 1/6 * 16 * 16 * (16-RL) ............ (Equation 39-1)

Next, the triangular pyramid shown in FIG.
This is shown in FIG. When the triangular pyramid shown in FIG. 31 (a) is viewed from the right, it can be shown as shown in FIG. 31 (b). Therefore, the volume Vc of the triangular pyramid shown in FIG.
Can be shown as follows. Vc = 1/3 * (16 * 16 * SQRT (2)) / 2 * (GL-BL) / SQRT (2) = 1/6 * 16 * 16 * (GL-BL) ............ (Equation 39- 2)

Next, the volume V of the triangular pyramid shown in FIG.
d can be expressed as follows. Vd = 1/3 * (16 * 16) / 2 * BL = 1/6 * 16 * 16 * BL ............ (Equation 39-3)

From the above (Equations 39-1) to (Equation 39-3), the volume Vb of the triangular pyramid shown in FIG. 30B can be expressed as follows. Vb = Overall product-(Va + Vc + Vd) = 1/6 * 16 * 16 * {16- (16-RL)-(GL-BL) -BL} = 1/6 * 16 * 16 * (RL- GL) ... (Equation 39-4)

As a result, the ratio of the volumes Va to Vd of the triangular pyramids shown in FIGS. 30A to 30D can be expressed as follows. Va: Vb: Vc: Vd = 16-RL: RL-GL: GL-BL: BL (Equation 39-5) Therefore, the lower 4 bits of the RGB signal, that is, (R
L, GL, BL) by volume ratio Va: Vb: Vc:
Vd is the weight coefficient W in the triangular pyramid.

Therefore, according to the relationship of RL ≧ GL ≧ BL and (Equation 30-1) to (Equation 30-4), the weight coefficient W
(W1 to w4) can be shown as follows. w1: w2: w3: w4 = 16-RL: RL-GL: GL-BL: BL (Equation 39-6)

[F] BL ≧ RL shown in FIG.
Weighting coefficient W in the case of ≧ GL (GL ≠ BL) FIG. 32 shows a triangular pyramid in the case of FIG. 16F, that is, in the case where the conversion point P satisfies BL ≧ RL ≧ GL.

As shown in FIGS. 33 (a) to (d), the triangular pyramid shown in FIG. 32 is further divided into four triangular pyramids based on the transformation point P, and the volumes Va to Vd
Is calculated. First, the volume V of the triangular pyramid shown in FIG.
a can be shown as follows. Va = 1/3 * (16 * 16) / 2 * (16-BL) = 1/6 * 16 * 16 * (16-BL) ............ (Equation 40-1)

Next, the triangular pyramid shown in FIG.
This is shown in FIG. When the triangular pyramid shown in FIG. 34A is viewed from above, it can be seen as shown in FIG. 34B. Therefore, the volume Vc of the triangular pyramid shown in FIG.
Can be shown as follows. Vc = 1/3 * (16 * 16 * SQRT (2)) / 2 * (RL-GL) / SQRT (2) = 1/6 * 16 * 16 * (RL-GL) ............ (Equation 40- 2)

Next, the volume V of the triangular pyramid shown in FIG.
d can be expressed as follows. Vd = 1/3 * (16 * 16) / 2 * GL = 1/6 * 16 * 16 * GL ... (Equation 40-3)

From the above (Equation 40-1) to (Equation 40-3), the volume Vb of the triangular pyramid shown in FIG. 33B can be expressed as follows. Vb = Overall product-(Va + Vc + Vd) = 1/6 * 16 * 16 * {16- (16-BL)-(RL-GL) -GL} = 1/6 * 16 * 16 * (BL- RL) ... (Equation 40-4)

As a result, the ratio of the volumes Va to Vd of the triangular pyramids shown in FIGS. 33A to 33D can be expressed as follows. Va: Vb: Vc: Vd = 16-BL: BL-RL: RL-GL: GL (Equation 40-5) Therefore, the lower 4 bits of the RGB signal, that is, (R
L, GL, BL) by volume ratio Va: Vb: Vc:
Vd is the weight coefficient W in the triangular pyramid.

Therefore, according to the relationship of BL ≧ RL ≧ GL and (Equation 30-1) to (Equation 30-4), the weight coefficient W
(W1 to w4) can be shown as follows. w1: w2: w3: w4 = 16-BL: BL-RL: RL-GL: GL (Equation 40-6)

Next, similarly to the cubic interpolation in the first embodiment, the weight coefficients W (w1 to
Consider the order in which w4) is stored. Also in the triangular pyramid interpolation, similarly to the cubic interpolation in the first embodiment, the weight coefficients W (w1 to w4) are continuously stored. That is, as shown in FIG. 35, when the lower 4 bits of the color image data output from the reading unit 14, that is, each of the RGB signals is (RL, GL, BL),
(0,0,0), (1,0,0), (2,0,0),.
.., (15, 15, 14) and (15, 15, 15) in the order of respective lattice points, the corresponding weighting factors W (w1 to w1)
w4) is stored continuously.

Specifically, a weighting coefficient W (w1 to w4) is stored for (0, 0, 0). Then, (1,
A weight coefficient W (w1 to w4) is stored for (0, 0). And finally, for (15,15,15),
The weight coefficients W (w1 to w4) are stored.

Therefore, the reference address L of the weight coefficient w1
ADR (w1) can be expressed as follows. LADR (w1) = RL + GL * 16 + BL * 16 ^ 2 * 4 = RL + GL * 16 + BL * 256 * 4 (Equation 41-1) Further, the reference address LADR of the weighting factors w2 to w4.
(N) (where N = w2 to w4) can be shown as follows. LADR (w2) = RL + GL * 16 + BL * 16 ^ 2 * 4 + 1 = LADR (A) +1 (Equation 41-2)

LADR (w3) = RL + GL * 16 + BL * 16 ^ 2 * 4 + 2 = LADR (A) +2 (Formula 41-3) LADR (w4) = RL + GL * 16 + BL * 16 ^ 2 * 4 + 3 = LADR (A) +3 (Equation 41-4) Therefore, if the reference address LADR (w1) of the weighting coefficient w1 is known by storing as above, three times. By simply incrementing, all weighting factors W (w1 to w4) can be sequentially obtained.

Next, similarly to the cubic interpolation in the first embodiment, in the case of triangular pyramid interpolation, the grid point “A
The order in which the grid point data of “〜H” is stored will be considered. As shown in FIG. 16, the triangular pyramid divided into six is one of the eight grid points “A to H” constituting the cube.
The lattice point “A” and the lattice point “H” are always included. That is, all the triangular pyramids divided into six are composed of the lattice point “A, H” and two lattice points of the other lattice points “B to G”.

In the triangular pyramid interpolation, the grid points "A, H"
And interpolation calculation processing is performed from the grid point data including the two grid points among the grid points “B to G”. Therefore,
In order to determine one triangular pyramid from the triangular pyramids divided into six, the lower 4 bits of the RGB signal, that is, the magnitude relation of each value of (RL, GL, BL) is determined. There is a need.

Therefore, the offset of the reference address at the lattice point of the triangular pyramid determined based on the magnitude relation of the values of (RL, GL, BL) will be examined. [A] In the case of a triangular pyramid of BL>GL> RL (FIG. 16 (a)
(See reference.) The lattice points constituting this triangular pyramid are “A, B, D, H”. For this reason, each grid point “A, B, D,” from the reference address of the grid point “A” in the reference “C” component
The offset of “H” is calculated by the above (Equation 1-1) to (Equation 1-8)
Therefore, they are "0,289,306,307", respectively.

[B] In the case of a triangular pyramid of GL>RL> BL (see FIG. 16B) The lattice points constituting this triangular pyramid are “A, C, G, H”. Therefore, each of the grid points “A, C, G, and” from the reference address of the grid point “A” in the reference “C” component
The offset of “H” is calculated by the above (Equation 1-1) to (Equation 1-8)
Thus, they are "0, 17, 18, 307", respectively.

[C] In the case of a triangular pyramid of RL>BL> GL (see FIG. 16 (c)) The lattice points constituting this triangular pyramid are “A, E, F, H”. Therefore, each of the grid points “A, E, F, and” from the reference address of the grid point “A” in the reference “C” component
The offset of “H” is calculated by the above (Equation 1-1) to (Equation 1-8)
Thus, they become "0, 1, 290, 307", respectively.

[D] GL ≧ BL ≧ RL (where RL ≠ G
L) Triangular pyramid (see FIG. 16 (d)) The lattice points constituting this triangular pyramid are "A, C, D, H". For this reason, each grid point “A, C, D,” from the reference address of the grid point “A” in the reference “C” component
The offset of “H” is calculated by the above (Equation 1-1) to (Equation 1-8)
Thus, they are "0, 17, 306, 307", respectively.

[E] In the case of a triangular pyramid of RL ≧ GL ≧ BL (see FIG. 16 (e)) The lattice points constituting this triangular pyramid are “A, E, G, H”. Therefore, each of the grid points “A, E, G, and” from the reference address of the grid point “A” in the reference “C” component
The offset of “H” is calculated by the above (Equation 1-1) to (Equation 1-8)
Thus, they are "0, 1, 18, 307", respectively.

[F] BL ≧ RL ≧ GL (where GL ≠ B
L) Triangular pyramid (see FIG. 16 (f)) The lattice points constituting this triangular pyramid are "A, B, F, H". Therefore, each grid point “A, B, F,...” From the reference address of the grid point “A” in the reference “C” component
The offset of “H” is calculated by the above (Equation 1-1) to (Equation 1-8)
Thus, they are "0, 29, 289, 307", respectively.

Therefore, in the case of the triangular pyramids shown in [a] to [f], similarly to the case of the cubic interpolation in the first embodiment, the reference address of the grid point “A” in the “C” component is used as a reference. Then, the offset of the reference address at the lattice points “BH” differs depending on the lattice points “BH”.
In addition, a method of judging the magnitude relation of each value of (RL, GL, BL) using a comparison instruction is also conceivable. However, when judging the magnitude relation using software, the use of the comparison instruction as a whole apparatus Processing speed slows down.

Therefore, [a] to [f] (FIG. 16)
The cases of the triangular pyramids (a) to (f)) are defined as follows using the offset “X”, respectively. [A] In the case of a triangular pyramid of BL>GL> RL, in other words, in the case of a triangular pyramid composed of lattice points “A, B, D, H”: X = 0 (Equation 42-1) b] In the case of a triangular pyramid of GL>RL> BL, in other words, in the case of a triangular pyramid composed of lattice points “A, C, G, H”: X = 1 (Equation 42-2) [c] ] RL>BL> GL, that is, a triangular pyramid composed of lattice points “A, E, F, H”: X = 2 (Equation 42-3)

[D] In the case of a triangular pyramid of GL ≧ BL ≧ RL, RL ≠ GL, in other words, in the case of a triangular pyramid composed of lattice points “A, C, D, H”: X = 3 (Equation 42-4) [e] In the case of a triangular pyramid of RL ≧ GL ≧ BL, in other words, in the case of a triangular pyramid composed of lattice points “A, E, G, H”: X = 4 (X = 4) Equation 42-5) [f] In the case of a triangular pyramid of BL ≧ RL ≧ GL, GL ≠ BL, in other words, in the case of a triangular pyramid composed of lattice points “A, B, F, H”: X = 5 ... (Equation 42-6)

Then, as shown in FIG. 36, [a] to
In the case of [f], that is, the offset “X” determined by the magnitude relationship of (RL, GL, BL) is stored as an LUT. By storing in this way, the magnitude relation of each value of (RL, GL, BL) can be determined without using a comparison instruction, and
It is possible to determine which of the triangular pyramids the conversion point P corresponds to.

Next, the order of storing grid point data at the four grid points forming the triangular pyramid will be discussed.
As shown in FIG. 37, each of the upper 4 bits of the RGB signal
Is (RH, GH, BH), (0,0,0),
(1,0,0), (2,0,0), ..., (15,1
5,14) and (15,15,15) in the order of four grid points for each of CMYK.
H "," A, C, G, H "," A, E, F, H ",
"A, C, D, H", "A, E, G, H", "A, B,
F, H "is stored.

Specifically, first, for (0, 0, 0), the grid point data of the grid point “A, B, D, H” corresponding to the “C” component, and the grid point data corresponding to the “M” component The grid points "A, B,
D, H "grid point data," Y "component corresponding grid point data" A, B, D, H "grid point data," K "component corresponding grid point data" A, B, D, H " Is stored.

Subsequently, “C” is assigned to (0, 0, 0).
Grid point data of grid points "A, C, G, H" corresponding to the component, grid point data of grid points "A, C, G, H" corresponding to the "M" component, and corresponding to the "Y" component The grid points "A, C,
G, H ”and the grid point data of the grid points“ A, C, G, H ”corresponding to the“ K ”component are stored.

Next, for (0, 0, 0), the grid point data of the grid point “A, E, F, H” corresponding to the “C” component, and the grid point “ A, E, F, H "grid point data, and grid points" A, E,
The grid point data of “F, H” and the grid point data of the grid points “A, E, F, H” corresponding to the “K” component are stored.

Finally, with respect to (15, 15, 15), the grid points “A, B, F, H” corresponding to the “C” component
Grid point data, grid points “A,
B, F, H ”grid point data, the grid point data“ A, B, F, H ”corresponding to the“ Y ”component, the grid point data“ A, B, F, H ”is stored.

By storing in this way, the grid point data to be stored increases, but the grid point “A” in the “C” component
Is determined, the other three grid points “X1, X2, H” that form the triangular pyramid (where X1 and X2 are grid points “B to G”) are merely incremented sequentially. 2) reference address can be obtained. Therefore, the grid point data of (RH, GH, BH) is not (0, 0, 0) to (16, 16, 16), but (0, 0, 0) to (15). ,
It is only necessary to store the grid point data up to 15, 15).

Therefore, the grid point “A” in the “C” component
Of the reference address HADR (A) can be expressed as follows. HADR (A) = (RH + GH * 16 + BH * 16 ^ 2) * 4 * 4 * 6 + 4 * 4 * X = (RH + GH * 16 + BH * 256) * 96 + 16 * X …… … (Equation 43)

By the way, as shown in FIG. 37, two of the four lattice points constituting the triangular pyramid, "A,
“H” is irrelevant to the magnitude relationship between the lower 4 bits of the RGB signal, ie, the values of (RL, GL, BL). In other words, the grid point data of grid point “A, H” is
In any of the above triangular pyramids [a] to [f],
This is grid point data that is essential for triangular pyramid interpolation calculations. Therefore, the remaining two grid points used for triangular pyramid interpolation are selected from the six grid points “B to G”. That is, grid point data necessary for triangular pyramid interpolation is grid point “A, H” and grid point “X1, X2” (where X1, X2 are grid points “B to
G ”). Specifically, among the grid points “B to G”, the grid points combined with the grid point “A, H” are “B, D”, “C, G”, “E,
F "," C, D "," E, G "," B, F ".

Therefore, the grid point data of the grid point "A, H" is stored as one set. Subsequently, the grid point data of the grid points “B, D” is stored as one set. Hereinafter, similarly, the grid points “C, G” and the grid points “E,
F, the grid points "C, D", the grid points "E, G", and the grid point data "B, F" are stored as one set.

That is, as shown in FIG. 38, if each of the upper 4 bits of the RGB signal is (RH, GH, BH), (0, 0, 0), (1, 0, 0), (2) , 0,
0),..., (15, 15, 14), (15, 15,
15) In the order of the grid points, grid points “A, H”, grid points “B, D”, grid points “C, G”, grid points “E, F”, grid points “C, D ", the grid point" E,
G "and grid point data of grid points" B, F "are stored as one set.

Specifically, first, for (0, 0, 0), the grid point data of the grid point “A, H” corresponding to the “C” component and the grid point “A” corresponding to the “M” component , H ", the grid point data of the grid point" A, H "corresponding to the" Y "component, and the grid point data of the grid point" A, H "corresponding to the" K "component.

Subsequently, for (1, 0, 0), "C"
Grid point data of grid points "B, D" corresponding to the components,
Grid point data of grid points “B, D” corresponding to “M” component, grid point data of grid points “B, D” corresponding to “Y” component, grid point “B, D” corresponding to “K” component D ”is stored.

Finally, for (15, 15, 15), the grid point data of the grid point “B, F” corresponding to the “C” component, and the grid point “B, F” corresponding to the “M” component , The grid point data of the grid point “B, F” corresponding to the “Y” component, and the grid point data of the grid point “B, F” corresponding to the “K” component.

With this storage, the grid point data of the four grid points "A, X1, X2, H" constituting the triangular pyramid cannot be stored continuously, but the storage order shown in FIG. In comparison with (RH, GH, BH), only one grid point data of the grid point “A, H” is stored. As a result, the number of grid point data to be stored can be reduced as compared with the storage order shown in FIG.

Therefore, the grid point “A” in the “C” component
Of the reference address HADR (A) can be expressed as follows. HADR (A) = (RH + GH * 16 + BH * 16 ^ 2) * 16 = (RH + GH * 16 + BH * 256) * 16 (Equation 44-1) Therefore, in the “C” component The reference address HADR (H) of the grid point “H” can be represented as follows. HADR (H) = (RH + GH * 16 + BH * 16 ^ 2) * 16 + 1 = HADR (A) +1 ............ (Formula 44-2)

The grid points “B to B” in the “C” component
The reference address HADR (BG) of "G" can be indicated as follows. HADR (BG) = (RH + GH * 16 + BH * 16 ^ 2) * 14 * 4 + 8 * (X + 1) = (RH + GH * 16 + BH * 256) * 56 + 8 * (X + 1) ...... (Equation 45)

Further, among the grid points "BG", (R
Assuming that two grid points determined by the magnitude relation of (L, GL, BL) are “X1, X2”, reference addresses HADR (X1), HA of the grid point “X1, X2” in the “C” component
DR (X2) can be expressed as follows. HADR (X1) = (RH + GH * 16 + BH * 16 ^ 2) * 14 * 4 + 8 * (X + 1) = (RH + GH * 16 + BH * 256) * 56 + 8 * (X + 1) ...... (Equation 46-1) HADR (X2) = (RH + GH * 16 + BH * 16 ^ 2) * 14 * 4 + 8 * (X + 1) +1 = (RH + GH * 16 + BH * 256) * 56 + 8 * (X + 1) +1 ............ (Equation 46-2)

It should be noted that “X” shown in (Equation 45), (Equation 46-1) and (Equation 46-2) is (RL, GL, BL)
Is defined by the magnitude relation between the values of (RL), (GL, BL), and specifically, the definition of the above (Equation 42-1) to (Equation 42-6) by the magnitude relation of each value of (RL, GL, BL) Determined by the formula. The offset “X” is also determined according to each value of (RL, GL, BL) shown in FIG.

Therefore, the grid point “A” in the “C” component
The reference address HADR (A) of the formula
Can be calculated from Further, the reference address HADR (H) of the grid point “H” in the “C” component is, as apparent from the above (Equation 44-2), the above (Eq.
It can be obtained by incrementing 1). Further, the grid points “A, H” in “M, Y, K”
Can also be obtained by sequentially incrementing (Equation 44-1).

In addition, the grid point “X” in the “C” component
The reference address HADR (X1) of “1”
-1) can be calculated. The reference address HA of the grid point “X2” in the other “C” component
DR (X2) can be obtained by incrementing (Equation 46-1) as is clear from (Equation 46-2). Further, the grid points “X1, X2” in “M, Y, K” can also be obtained by incrementing the above (Equation 46-1).

Next, the interpolation value I of the “C, M, Y, K” component
A method of calculating PL (N) (where N = C, M, Y, K) will be described. The color image data output from the reading unit 14, that is, each of the lower 4 [bi] of the RGB signal
t] is (RL, GL, BL), and (RL, GL, BL)
Assuming that “LL, LM, LS” is in descending order of each value of BL), the interpolation value IPL (N) of the “C, M, Y, K” component (where N = C, M, Y, K) is Similar to the cubic interpolation in the first embodiment, the following can be shown. IPL (N) = {(16-LL) * f (A) + (LL-LM) * f (X1) + (LM-LS) * f (X2) + LS * f (H)} / 16 …… … (Equation 47)

Note that “X1, X2” shown in (Equation 47)
Are two of the grid points “B to G” determined by the magnitude relation of the values of (RL, GL, BL). Also, (Equation 4
F (A), f (X1), f (X2) and f shown in 7)
(H) is obtained by using the above (Formula 44-1) and the above (Formula 46-1)
"C, M, obtained by the increment
This is the grid point data of the grid point “A, X1, X2, H” in the “Y, K” component.

Next, the case where the conversion point P corresponds to the exception processing in the triangular pyramid interpolation will be described. Similarly to the case of the cube interpolation in the first embodiment, the case corresponding to the exceptional processing in the triangular pyramid interpolation means that the upper 4 bits of the RGB signal in the cube shown in FIG. 8 are set to (RH, GH). , BH), the (RH, GH, B)
This is a case where any one of the values of H) is “15”.

Therefore, when the conversion point P corresponds to the exception processing, the following “seven patterns” are performed as in the case of the cubic interpolation in the first embodiment. [1] RH = 15, GH <15, BH <15 (E1 shown in FIG. 8) [2] RH <15, GH = 15, BH <15 (E2 shown in FIG. 8) [3] RH <15 , GH <15, BH = 15 (E3 shown in FIG. 8) [4] RH = 15, GH = 15, BH <15 (E4 shown in FIG. 8) [5] RH <15, GH = 15, BH = 15 (E5 shown in FIG. 8) [6] RH = 15, GH <15, BH = 15 (E6 shown in FIG. 8) [7] RH = 15, GH = 15, BH = 15 (FIG. 8 E7 shown in)

However, in the triangular pyramid interpolation, the cube is further divided into six to obtain a triangular pyramid. In other words, as shown in FIG.
If [bit] is (RL, GL, BL), then (R
(L, GL, BL), the cube is further divided into six parts to obtain a triangular pyramid. That is, (R
L, GL, BL) have the following relationship. [A] When BL>GL> RL [b] When GL>RL> BL [c] When RL>BL> GL [d] When GL ≧ BL ≧ RL (where RL ≠ GL) [e] When RL ≧ GL ≧ BL [f] When BL ≧ RL ≧ GL (GL ≠ BL)

As a result, in the triangular pyramid interpolation, if it corresponds to the exception processing, “RL”, “RL”, and “B” are added according to the possible values of each value of (RH, GH, BH).
There are “six types” depending on the magnitude relation of each value of L). Therefore, in the triangular pyramid interpolation, when the conversion point P corresponds to the exception processing, “7 patterns” * “6 patterns” = “42 patterns”.

Therefore, [1] RH = 15, GH <1
5, BH <15, and [e] RL ≧ G
The weight coefficient W (w1 to w4) in the case of L ≧ BL is calculated. FIG. 39 shows that RH = 15, GH <15, BH <
15 shows a triangular pyramid in the case of RL ≧ GL ≧ BL.

Therefore, as shown in FIGS. 40 (a) to (d), the triangular pyramid shown in FIG. 39 is further divided into four triangular pyramids based on the transformation point P, and the volume of each triangular pyramid is V
a to Vd are calculated. First, the volume Va of the triangular pyramid shown in FIG. 40A can be shown as follows. Va = 1/3 * (16 * 16) / 2 * (15-RL) = 1/6 * 16 * 15 * (16-16 * RL / 15) ............ (Equation 48-1)

Next, the triangular pyramid shown in FIG.
This is shown in FIG. When the triangular pyramid shown in FIG. 41 (a) is viewed from the right, it can be shown as shown in FIG. 41 (b). For this reason, the volume Vc of the triangular pyramid shown in FIG.
Can be shown as follows. Vc = 1/3 * (16 * 15 * SQRT (2)) / 2 * (GL-BL) / SQRT (2) = 1/6 * 16 * 15 * (GL-BL) ............ (Equation 48- 2)

Next, the volume V of the triangular pyramid shown in FIG.
d can be expressed as follows. Vd = 1/3 * (16 * 15) / 2 * BL = 1/6 * 16 * 15 * BL (Equation 48-3)

From the above (Equation 48-1) to (Equation 48-3), the volume Vb of the triangular pyramid shown in FIG. 40B can be expressed as follows. Vb = Overall product-(Va + Vc + Vd) = 1/6 * 16 * {16 * 15-16 * (15-RL) -15 * (GL-BL) -15 * BL} = 1/6 * 16 * 15 * (16 * RL / 15-GL) ............ (Equation 48-4)

As a result, the ratio of the volumes Va to Vd of the triangular pyramids shown in FIGS. 40A to 40D can be expressed as follows. Va: Vb: Vc: Vd = 16-16 * RL / 15: 16 * RL / 15-GL: GL-BL: BL (Equation 48-5) Therefore, the lower 4 bits of the RGB signal, that is, (R
L, GL, BL) by volume ratio Va: Vb: Vc:
Vd is the weight coefficient W in the triangular pyramid.

Therefore, according to the relationship of RL ≧ GL ≧ BL and (Equation 30-1) to (Equation 30-4), the weight coefficient W
(W1 to w4) can be shown as follows. w1: w2: w3: w4 = 16-16 * RL / 15: 16 * RL / 15-GL: GL-BL: BL (Equation 48-6)

Next, [5] RH <15, GH = 15, B
H = 15 and [c] RL>BL> G
The weight coefficient W (w1 to w4) in the case of L is calculated. FIG. 42 shows that RH <15, GH = 15, BH = 15
And a triangular pyramid in the case of RL>BL> GL.

Therefore, as shown in FIGS. 43 (a) to 43 (d), the triangular pyramid shown in FIG. 42 is further divided into four triangular pyramids based on the conversion point P, and the volume of each triangular pyramid is V
a to Vd are calculated. First, the volume Va of the triangular pyramid shown in FIG. 43A can be expressed as follows. Va = 1/3 * (15 * 15) / 2 * (16-RL) = 1/6 * 15 * 15 * (16-RL) ... (Equation 49-1)

Next, the triangular pyramid shown in FIG.
This is shown in FIG. When the triangular pyramid shown in FIG. 44 (a) is viewed from the right, it can be shown as shown in FIG. 44 (b). Therefore, the volume Vc of the triangular pyramid shown in FIG.
Can be shown as follows. Vc = 1/3 * (16 * 15 * SQRT (2)) / 2 * (BL-GL) / SQRT (2) = 1/6 * 15 * 15 * (16 * BL / 15-16 * GL / 15 ) (Equation 49-2)

Next, the volume V of the triangular pyramid shown in FIG.
d can be expressed as follows. Vd = 1/3 * (16 * 15) / 2 * GL = 1/6 * 15 * 15 * (16 * GL / 15) (Equation 49-3) From Equation 49-3), FIG.
The volume Vb of the triangular pyramid shown in (b) can be shown as follows. Vb = Overall product-(Va + Vc + Vd) = 1/6 * 15 * {16 * 15-15 * (16-RL) -16 * (BL-GL) -16 * GL} = 1/6 * 15 * 15 * (RL-16 * BL / 15) ............ (Equation 49-4)

As a result, the ratio of the volumes Va to Vd of the triangular pyramids shown in FIGS. 43A to 43D can be expressed as follows. Va: Vb: Vc: Vd = 16-RL: RL-16 * BL / 15: 16 * BL / 15-16 * GL / 15: 16 * GL / 15 (Equation 49-5) Therefore, the RGB signal The lower 4 bits of (R)
L, GL, BL) by volume ratio Va: Vb: Vc:
Vd is the weight coefficient W in the triangular pyramid.

Therefore, according to the relationship of RL>BL> GL and (Equation 30-1) to (Equation 30-4), the weight coefficient W
(W1 to w4) can be shown as follows. w1: w2: w3: w4 = 16-RL: RL-16 * BL / 15: 16 * BL / 15-16 * GL / 15: 16 * GL / 15 ............ (Equation 49-6)

Here, based on the above two examples, the weight coefficient W (w1 to w4) when the exception processing is not applied and the weight coefficient W (w1 to w4) when the exception processing is applied are compared and examined. I do.

More specifically, the weighting factor W (w1 to w
(4) and the weighting coefficient W (w in the case of RL ≧ GL ≧ BL in the case of exception processing.
Comparing with (Equation 48-6) showing (1 to w4), (Equation 48-6) is obtained by substituting “16 * RL / 15” for “RL” in (Equation 39-6). You can see that there is.

The above equation (37-6) indicating the weight coefficient W (w1 to w4) when RL>BL> GL when the exception processing does not apply, and RL>BL> when the exception processing applies. Weight coefficient W (w1 to w
Comparing and examining the above (Equation 49-6) showing 4),
(Equation 49-6) is obtained by adding “16” to “GL” of (Equation 37-6).
It can be seen that * GL / 15 is substituted for "16 * BL / 15" for "BL".

As described above, (Equation 39-6) and (Equation 48-6), (Equation 37-6) and (Equation 49-6) shown in the two examples
As can be inferred from the above, in the exceptional processing of the triangular pyramid interpolation, the weight coefficient W (w1
To w4) (Formulas 35 to 40-6), (RH,
GH, BH) can be obtained by substituting the following relational expressions based on the possible values of the respective values.

[1] When RH = 15, GH <15, BH <15 RL ← 16 * RL / 15 (Equation 50) [2] GL when RH <15, GH = 15, BH <15 ← 16 * GL / 15 (Equation 51) [3] When RH <15, GH <15, BH = 15 BL ← 16 * BL / 15 (Equation 52) [4] RH = 15, When GH = 15, BH <15 RL ← 16 * RL / 15 (Equation 53-1) GL ← 16 * GL / 15 (Equation 53-2)

[5] When RH <15, GH = 15, BH = 15 GL ← 16 * GL / 15 (Expression 54-1) BL ← 16 * BL / 15 (Expression 54-2) [6] When RH = 15, GH <15, BH = 15 RL ← 16 * RL / 15 (Equation 55-1) BL ← 16 * BL / 15 (Equation 55-2) 7] When RH = 15, GH = 15, BH = 15 RL ← 16 * RL / 15 (Equation 56-1) GL ← 16 * GL / 15 (Equation 56-2) BL ← 16 * BL / 15 ............ (Equation 56-3)

Next, a method of determining whether the conversion point P corresponds to exception processing will be discussed. When the conversion point P corresponds to the exception processing, the upper 4 bits of the RGB signal at the conversion point P, that is, (RH, GH, BH), as in the case of the cubic interpolation in the first embodiment.
Can be determined based on whether or not any of the respective values is “15”.

As a result, the determination can be made in the same manner as in the case of the cubic interpolation in the first embodiment. Specifically, as shown in FIG. 9, the value indicating whether or not the exception processing is performed is “Z”, and the value of “Z” for (RH, GH, BH) is stored. Based on the value of “Z”, it can be determined whether or not the process corresponds to exception processing. Therefore, "Z" indicating whether or not it corresponds to exception processing
The reference address ZHADR (Z) can be expressed in the same manner as in the above (Equation 15).

Next, the order of storing the weighting factors W (w1 to w4) in the case of exception processing will be described with reference to the drawings. As shown in FIG. 45, the value indicating whether the process corresponds to the exception process is “Z”, and the data of the color image output from the reading unit 14, that is, the lower 4 bits of the RGB signal are (RL, GL). , BL), the weighting factor is “W”, and (RL, G) corresponding to each Z (= 0 to 7)
(L, BL). Also, (RL, GL, BL)
Are successively stored in the order of w1 to w4.

Specifically, a weighting coefficient W (w1 to w4) is stored for (0, 0, 0) when Z = "0". Subsequently, a weighting coefficient W (w1 to w4) is stored for (1, 0, 0). And finally, Z
Weight coefficients W (w1 to w4) are stored for (15, 15, 15) in the case of = “7”.

For this reason, the reference address ELADR (w1) of the weight coefficient W1 including the exception processing can be expressed as follows. ELADR (w1) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 4 = (RL + GL * 16 + BL * 256) * 8 + Z * 4096 * 4 …… ... (Equation 57-1)

Also, weighting factors w2 to w4 including exception processing
Reference address ELADR (N) (where N = w2 to w
4) can be shown as follows. ELADR (w2) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 4 + 1 = ELADR (w1) +1 ............ (Formula 57-2) ELADR (w3) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 4 + 2 = ELADR (w1) +2 ... (Equation 57-3) ELADR (w4) = (RL + GL * 16 + BL * 16 ^ 2) * 8 + Z * 16 ^ 3 * 4 + 3 = ELADR (w1) +3 ... (Equation 57-4)

Therefore, by storing in this way, if the reference address ELADR (w1) of the weight coefficient w1 is known, 3
By simply incrementing the number of times, all the weighting factors W (w
1 to w4) can be sequentially obtained.

Next, in the exception processing, “C, M, Y,
K ”component interpolation value IPL (N) (where N = C, M,
(Y, K) will be described. That is,
In the exception processing, there are "seven patterns" depending on the possible values of (RH, GH, BH) and "six patterns" depending on the magnitude relationship of the values of (RL, GL, BL). Therefore, when the exception processing is applied, (RH, G) is added to the above (Equation 47) indicating the interpolation value IPL (N) when the exception processing is not applied.
H, BH) can be obtained by substituting the relational expressions (Equation 50) to (Equation 56-3) determined based on the possible values of the respective values of (H, BH).

Next, in the facsimile machine 1, when the RGB signal of the conversion point P is output from the reading unit 14,
The operation of the color conversion processing for pixels will be described with reference to the flowchart shown in FIG. 11 in the first embodiment. This operation is performed under the control of the MPU 11 based on a program stored in the ROM 12.

In step S1 shown in FIG. 11, the lower 4 bits, ie, (RL, GL, BL), are extracted from the RGB signal at the conversion point P. In step S2, (RL,
GL, BL), the reference address LADR (w1) of the weight coefficient (w1) is calculated. Specifically, the reference address LADR (w1) of the weight coefficient w1 is calculated based on the above (Equation 41-1).

In step S3, the weighting factors W (w1 to w4) of the triangular pyramid surrounding the transformation point P are stored in the ROM.
12 are sequentially read. Specifically, the reference address LADR (w1) calculated in step S2
Are sequentially incremented, and all weighting factors W
(W1 to w4) are weighting factors W (w1
To w4) are sequentially read from the LUT.

In step S4, the RG of the conversion point P
The upper 4 bits from the B signal, that is, (RH, G
H, BH) are extracted. In step S5, (RH, GH, B
Based on H), the reference address HADR (A) of the grid point “A” in the “C” component is calculated. In particular,
First, the offset “X” determined by the magnitude relationship between the values of (RL, GL, BL) shown in FIG. 36 is read. Then, the reference address HADR (A) of the grid point “A” in the “C” component is calculated based on the above (Equation 43).

In step S6, the grid points "A, X1, X2, H" in the triangular pyramid surrounding the conversion point P (where X1 and X2 are two of the grid points "B to G", in other words, For example, two of the grid points "BG" determined by the offset "X" in step S5 are stored in the ROM1.
2 are sequentially read. Specifically, the step S
Grid point “A” in the “C” component calculated in 5
Are sequentially incremented from the reference address HADR (A) of the grid point “A, X1, X2,
The grid point data “H” is sequentially read from the grid point data LUT shown in FIG.

In step S7, an interpolation operation at the conversion point P is performed. Specifically, step S3
Based on the weighting factors W (w1 to w4) read out at step S6 and the grid point data of the grid points “A, X1, X2, H” in the “C” component read at step S6. The interpolation operation at the conversion point P is performed by Expression 47).

In step S8, it is determined whether there is a next component. Specifically, the interpolation operation of the “M” component is performed when the interpolation operation of the “C” component is performed, and the interpolation operation of the “Y” component and the “Y” component is performed when the interpolation operation of the “M” component is performed. In this case, it is determined whether or not there is a “K” component. If there is a next component, the process proceeds to step S9. On the other hand, when there is no next component, that is, all “C, M,
When the interpolation calculation is completed for the “Y, K” components,
This processing ends.

In step S9, the reference address of grid point "A" in the next component is calculated. Specifically, as shown in FIG. 37, the grid point data of the grid points “A, X1, X2, H” is stored for the “C, M, Y, K” components. It only needs to sequentially increment the reference address HADR (A) of the grid point “A” in the “C” component calculated in step S5. Then, steps S6 to S9 are repeatedly executed, and the interpolation calculation of “M, Y, K” at the conversion point P is performed. That is, steps S6 to S9 are repeatedly executed, and “C, M, Y,
The interpolation operation of the “K” component is performed, and the RGB signals at the conversion point P are converted into CMYK signals. In general, since there are a large number of pixels to be converted, this process is repeatedly performed on all the read pixels.

As described above in detail, according to the fourth embodiment, the following operation and effect can be obtained in addition to the operation and effect of the first embodiment. (1) In the fourth embodiment, the LUT of the lattice point data shown in FIG. 37, which has a large amount of lattice point data to be stored, is used instead of the LUT of the lattice point data shown in FIG. It is the reference address HAD of the grid point "A".
This is because, if R (A) is calculated, grid point data at the other four grid points forming the triangular pyramid can be obtained only by sequentially incrementing. In other words, when the LUT of the grid point data shown in FIG.
-1) and (Equation 45), the reference address HADR (A) of the grid point “A” and the reference address HADR (X1) of the grid point “X1” must be calculated. Then, these reference addresses HADR (A) and HADR (A)
The increment must be performed from (X1) to obtain grid point data of grid points “H” and “X2”. For this reason, the LUT of the grid point data shown in FIG. 37 is used. Therefore, even in the case of triangular pyramid interpolation,
Color conversion processing can be performed at high speed using software.

(2) In the fourth embodiment, since triangular pyramid interpolation is used, the data required for the interpolation calculation process is four for each of the lattice point data and the weight coefficient W. That is, the grid point data of the grid points “A, X1, X2, H” and the weighting factors W (w1 to w4). For this reason, although the accuracy of the interpolation calculation result of the conversion point P is inferior to the case of the cubic interpolation in the first to third embodiments, the amount of data to be read is reduced, so that the color conversion processing can be performed at higher speed. Can be.

(3) As is clear from the above (Equation 47), in the calculation processing of triangular pyramid interpolation, the product-sum
[Times] Have been performed. Therefore, the color conversion processing can be performed at a higher speed than in the case of the cubic interpolation in the first to third embodiments.

(4) Even in the case of triangular pyramid interpolation, FIG. 11 used in the cubic interpolation in the first embodiment is used.
Can be applied.
Therefore, the processing of the flowchart shown in FIG. 11 can easily correspond to various interpolation calculation methods.

[Fifth Embodiment] In the Case of Triangular Pyramid Interpolation (Four-Point Interpolation) In the fifth embodiment, the configuration similar to that of the first embodiment is the same as that of the first embodiment. And the description is omitted. In the fifth embodiment, a case corresponding to exception processing in the fourth embodiment is considered. Therefore, in the fifth embodiment, the ROM 12 stores the LUT for determining whether the conversion point P shown in FIG. 9 corresponds to the exception processing, and the values of (RL, GL, BL) shown in FIG. LUT determined by the magnitude relation of LUT and LUT of grid point data shown in FIG.
And the LUT of the weight coefficient W (w1 to w4) including the case corresponding to the exception processing shown in FIG.

Next, in the facsimile machine 1, when the RGB signal of the conversion point P is output from the reading unit 14,
FIGS. 12 and 13 show the operation of the color conversion processing for the pixels.
This will be described with reference to the flowchart shown in FIG. This operation is performed based on a program stored in the ROM 12 based on M
It is executed under the control of the PU 11.

In step S11 shown in FIG.
The upper 4 bits, that is, (RH, GH, BH) are extracted from the RGB signal at the conversion point P. Step S12
In, it is determined based on (RH, GH, BH) extracted in step S11 whether or not the conversion point P corresponds to exception processing. Specifically, the reference address ZHADR (Z) of “Z” indicating whether or not the exception processing is performed is calculated based on the above (Equation 15).
Then, the value of “Z” is extracted based on the reference address ZHADR (Z). Specifically, whether or not the conversion point P corresponds to the exception processing is determined based on the LUT for determining whether or not the conversion point P corresponds to the exception processing. That is, when the value of “Z” indicating whether or not the exception processing is performed is “1 to 7”, it is determined that the processing corresponds to the exception processing, and the process proceeds to step S31 illustrated in FIG. On the other hand, when the value of “Z” indicating whether or not the exception processing is performed is “0”, it is determined that the processing does not correspond to the exception processing, and
Move to step S13. Note that the above (Equation 15-1)
May be determined on the basis of the exception processing.

In the step S13, the R of the conversion point P
The lower 4 bits from the GB signal, that is, (RL, G
L, BL) are extracted. In step S14,
(RL, GL,
BL), the reference address ELADR (w1) of the weight coefficient (w1) including the case corresponding to the exception processing is calculated. Specifically, based on the above (Equation 57-1),
The reference address ELADR (w1) of the weight coefficient w1 is calculated.

In step S15, the weight coefficient W (w1 to w4) in the triangular pyramid surrounding the transformation point P is set to RO
They are sequentially read from M12. Specifically, the reference address ELADR (w calculated in step S4)
From 1), all the weighting factors W (w1 to w4) are read out from the LUT of the weighting factors W (w1 to w4) including the case corresponding to the exception processing shown in FIG. Specifically, the reference address ELADR of the weight coefficient w1 calculated in step S14
(W1) are sequentially incremented, and all the weighting factors W (w1 to w4) are LUTs of the weighting factors W (w1 to w4) including a case corresponding to the exception processing shown in FIG.
Are sequentially read out. More specifically, the weighting factors W (w1 to w1) including the case corresponding to the exception processing shown in FIG.
w4) In the LUT, step S shown in FIG.
The weighting coefficient W (w1 to w) corresponding to the value of “Z (= 0)” calculated based on the above (Equation 15) in the processing of No. 12
4) are sequentially read.

It should be noted that, instead of the processing of steps S14 and S15, the (R
L, GL, BL) based on the weighting factors W (w1 to w
4) may be calculated. Specifically, (RL, GL, B
L) based on the magnitude relationship between the values of (L)
-6), the weighting coefficient W (w1 to w4) may be calculated.

In step S16, the R of the conversion point P
The upper 4 bits from the GB signal, that is, (RH, G
H, BH) are extracted. Note that the upper 4 bits
Is the same processing as in step S11, so the top 4 [b] extracted in step S11
it] may be used as it is.

In step S17, the reference address HADR (A) of the grid point "A" in the "C" component is calculated based on (RH, GH, BH) extracted in step S16. Specifically, first, FIG.
6, the offset “X” determined by the magnitude relationship of the values of (RL, GL, BL) is read. Then, the reference address HADR (A) of the grid point “A” in the “C” component is calculated based on the above (Equation 43).

The reference address HADR (A) of the grid point “A” in the “C” component is the reference address ZHADR of “Z” calculated in step S12.
(Z), that is, a reference address ZHADR of “Z” indicating whether or not the exception processing shown in (Equation 15) is applicable.
After multiplying (Z) by “96”, the value of “16 * X” may be added to calculate the reference address HADR (A) of the grid point “A” in the “C” component.

In step S18, the lattice points “A, X1, X2, H” in the triangular pyramid surrounding the transformation point P
(However, X1 and X2 are two of the grid points “B to G”.
In other words, two of the grid points “B to G” determined by the offset “X” in step S17 are sequentially read from the ROM 12. More specifically, the grid point “A, X” of the “C” component is sequentially incremented from the reference address HADR (A) of the grid point “A” in the “C” component calculated in step S17.
The grid point data of “1, X2, H” is sequentially read from the grid point data LUT shown in FIG.

In step S19, an interpolation operation at the conversion point P is performed. Specifically, the step S
Weighting coefficient W (w1 to w4) read out at 15
Based on the grid point data of the grid points “A, X1, X2, H” in the “C” component read in step S18, the interpolation calculation at the conversion point P is performed by (Equation 47). Will be

In step S20, it is determined whether there is a next component. Specifically, the interpolation operation of the “M” component is performed when the interpolation operation of the “C” component is performed, and the interpolation operation of the “Y” component and the “Y” component is performed when the interpolation operation of the “M” component is performed. In this case, it is determined whether or not there is a “K” component.
If there is a next component, the process proceeds to step S21. On the other hand, when there is no next component, that is, when all “C,
When the interpolation calculation has been completed for the "M, Y, K" components, this processing ends.

In step S21, the reference address of grid point "A" in the next component is calculated. Specifically, as shown in FIG. 37, for the “C, M, Y, K” components, the grid points “A, B, D, H” and the grid points “A, C, G, H” , Grid points “A, E, F, H”, grid points “A, C, D, H”, grid points “A, E, G, H”, and grid points “A, B, F, H”. Since the grid point data is stored, “C” calculated in step S17 is used.
Address HADR of grid point "A" in the component
It is merely incremented sequentially from (A). Then, steps S18 to S21 are repeatedly executed, and the interpolation calculation of “M, Y, K” at the conversion point P is performed. That is, steps S18 to S21 are repeatedly executed, and “C, M, Y,
The interpolation operation of the “K” component is performed, and the RGB signals at the conversion point P are converted into CMYK signals.

In step S31 shown in FIG.
The lower 4 bits, that is, (RL, GL, BL), are extracted from the RGB signal at the conversion point P. Step S32
In the above, based on the (RL, GL, BL) extracted in the step S31, the reference address ELADR of the weight coefficient (w1) including the case corresponding to the exception processing
(W1) is calculated. Specifically, the above (Equation 57-
1), the reference address ELAD of the weight coefficient w1
R (w1) is calculated.

In step S33, the weight coefficient W (w1 to w4) in the triangular pyramid surrounding the transformation point P is set to RO
They are sequentially read from M12. Specifically, the weight coefficient w1 calculated in step S32 is sequentially incremented from the reference address ELADR (w1),
All the weighting factors W (w1 to w4) include the weighting factors W (w1 to w4
The data is sequentially read from the LUT of 4). More specifically,
In the LUT of the weight coefficient W (w1 to w4) including the case corresponding to the exception processing shown in FIG. 45, “Z (=) calculated based on the (Equation 15) in the processing of step S12 shown in FIG. 1 to 7) are sequentially read out.

Note that, instead of the processing of steps S32 and S33, the weighting factor W () is determined according to the value “Z” indicating whether or not the processing corresponds to the exception processing shown in the processing of step S2 shown in FIG. w1 to w4) may be calculated. Specifically, according to the case where the value “Z” indicating whether or not the exception processing is applicable is “1 to 7”, in other words, (RH, GH,
BH), (Equation 48-6) and (Equation 49-
6), the weighting coefficient W (w1
To w4) may be calculated.

In step S34, R of conversion point P
The upper 4 bits from the GB signal, that is, (RH, G
H, BH) are extracted. Note that the upper 4 bits
Is the same as step S11 shown in FIG. 12, and the upper 4 bits extracted in step S11 shown in FIG. 12 may be used as it is.

In step S35, the reference address HADR (A) of the grid point "A" in the "C" component is calculated based on the (RH, GH, BH) extracted in step S34. Specifically, first, FIG.
6, the offset “X” determined by the magnitude relationship of the values of (RL, GL, BL) is read. Then, the reference address HADR (A) of the grid point “A” in the “C” component is calculated based on the above (Equation 43).

The reference address HADR (A) of the grid point “A” in the “C” component is the reference address ZHADR of “Z” calculated in step S12.
(Z), that is, a reference address ZHADR of “Z” indicating whether or not the exception processing shown in (Equation 15) is applicable.
After multiplying (Z) by “96”, the value of “16 * X” may be added to calculate the reference address HADR (A) of the grid point “A” in the “C” component.

In step S36, the lattice points “A, X1, X2, H” in the triangular pyramid surrounding the transformation point P
(However, X1 and X2 are two of the grid points “B to G”.
In other words, two of the grid points “B to G” determined by the offset “X” in step S35 are sequentially read from the ROM 12. Specifically, the grid point “A, X” of the “C” component is sequentially incremented from the reference address HADR (A) of the grid point “A” of the “C” component calculated in step S35.
The grid point data of “1, X2, H” is sequentially read from the grid point data LUT shown in FIG.

At step S37, an interpolation operation at the conversion point P is performed. Specifically, the step S
Weighting coefficient W (w1 to w4) read out at 33
Based on the grid point data of the grid points “A, X1, X2, H” in the “C” component read in step S36, the interpolation calculation at the conversion point P is performed by (Equation 47). Will be

In step S38, it is determined whether there is a next component. Specifically, the interpolation operation of the “M” component is performed when the interpolation operation of the “C” component is performed, and the interpolation operation of the “Y” component and the “Y” component is performed when the interpolation operation of the “M” component is performed. In this case, it is determined whether or not there is a “K” component.
If there is a next component, the process proceeds to step S39. On the other hand, when there is no next component, that is, when all “C,
When the interpolation calculation has been completed for the "M, Y, K" components, this processing ends.

In step S39, the reference address of grid point "A" in the next component is calculated. Specifically, as shown in FIG. 37, for the “C, M, Y, K” components, the grid points “A, B, D, H” and the grid points “A, C, G, H” , Grid points “A, E, F, H”, grid points “A, C, D, H”, grid points “A, E, G, H”, and grid points “A, B, F, H”. Since the grid point data is stored, “C” calculated in step S35 is used.
Address HADR of grid point "A" in the component
It is merely incremented sequentially from (A). Then, steps S36 to S39 are repeatedly executed, and the interpolation calculation of “M, Y, K” at the conversion point P is performed. That is, steps S36 to S39 are repeatedly executed, and “C, M, Y,
The interpolation operation of the “K” component is performed, and the RGB signals at the conversion point P are converted into CMYK signals. In general, since there are a large number of pixels to be converted, this process is repeatedly performed on all the read pixels.

As described above in detail, according to the fifth embodiment, the following operation and effect can be obtained in addition to the operation and effect of the fourth embodiment. (1) In the fifth embodiment, as shown in FIG. 45, the weight coefficient W including the case corresponding to the exceptional processing is w1
Ｗw4 are stored in the ROM 12 in this order. For this reason, based on the above (Equation 57-1), the reference address ELADR of the weight coefficient w1 in the case of exception processing
Once (w1) is known, it is only necessary to increment sequentially,
Other weighting factors w2 to w4 can also be obtained. Therefore,
Even if the conversion point P corresponds to exception processing, RGB
When performing color conversion processing from a signal to a CMYK signal,
Even if software is used, color conversion processing can be performed at high speed. Moreover, even when the conversion point P corresponds to the exception processing, the color conversion processing can be executed without including an error.

[Sixth Embodiment] In the Case of Triangular Pyramid Interpolation (Four-Point Interpolation) In the sixth embodiment, the configuration similar to that of the first embodiment is the same as that of the first embodiment. And the description is omitted. In the sixth embodiment, as in the fifth embodiment, a case corresponding to exception processing in the fourth embodiment is considered. In addition, the sixth embodiment is different from the fifth embodiment in that the color conversion process is executed without determining whether or not the process corresponds to the exception process.

In the sixth embodiment, the ROM 12
Is an LUT for judging whether or not the conversion point P shown in FIG. 9 corresponds to exception processing, and FIG. 36 shows (RL, GL, B
L) of the offset determined by the magnitude relationship of each value of L)
T, LUT of grid point data shown in FIG. 37, and weighting factors W (w1 to w
4) The LUT is stored.

[0279] Next, in the facsimile apparatus 1, 1 when the RGB signal of the conversion point P is output from the reading unit 14
The operation of the color conversion process for pixels will be described with reference to the flowchart shown in FIG. Note that this operation is performed by the RO
The program is executed under the control of the MPU 11 based on the program stored in the M12.

In step S41 shown in FIG.
The upper 4 bits, that is, (RH, GH, BH) are extracted from the RGB signal at the conversion point P. Step S42
In, based on (RH, GH, BH) extracted in step S41, a reference address ZHADR (Z) of “Z” indicating whether or not an exception process is applicable is calculated. Specifically, based on the above (Equation 15), the reference address Z of “Z” indicating whether or not the exception processing is performed.
HADR (Z) is calculated.

In step S43, the reference address ZHA of "Z" calculated in step S42 is set.
The value of “Z” is extracted based on DR (Z). Specifically, the value of “Z” is extracted based on the LUT for determining whether the conversion point P shown in FIG. 9 corresponds to exception processing. Therefore, when the value of “Z” is “0”,
It can be determined that the conversion point P does not correspond to exception processing. When the value of “Z” is “1 to 7”, it can be determined that the conversion point P corresponds to exception processing,
It is possible to determine which of the seven exceptions [1] to [7] corresponds to the exception processing.

In step S44, the R of conversion point P
The lower 4 bits from the GB signal, that is, (RL, G
L, BL) are extracted. In step S45,
(RL, GL,
BL), the reference address E of the weight coefficient (w1)
LADR (w1) is calculated. Specifically, based on the above (Equation 57-1), the reference address E of the weight coefficient w1 is obtained.
LADR (w1) is calculated.

In step S46, the weight coefficient W (w1 to w4) in the triangular pyramid surrounding the transformation point P is set to RO
They are sequentially read from M12. Specifically, the weight coefficient w1 calculated in step S45 is sequentially incremented from the reference address ELADR (w1),
All the weighting factors W (w1 to w4) include the weighting factors W (w1 to w4
The data is sequentially read from the LUT of 4). More specifically,
In the weight coefficient W (w1 to w4) including the case corresponding to the exception processing shown in FIG. 45, the weight coefficient W corresponding to “Z (= 0 to 7)” extracted in the step S43.
(W1 to w4) are read.

[0284] In step S47, the R of the conversion point P
The upper 4 bits from the GB signal, that is, (RH, G
H, BH) are extracted. Note that the upper 4 bits
Is the same processing as in step S41, so the top 4 [b] extracted in step S41
it] may be used as it is.

In step S48, the reference address HADR (A) of the grid point "A" in the "C" component is calculated. Specifically, first, (RL, G
The offset “X” determined by the magnitude relationship between the values of (L, BL) is read. Then, the reference address HADR (A) of the grid point “A” in the “C” component is calculated based on the above (Equation 43).

The reference address HADR (A) of the grid point “A” in the “C” component is the reference address ZHADR of “Z” calculated in step S42.
(Z), that is, a reference address ZHADR of “Z” indicating whether or not the exception processing shown in (Equation 15) is applicable.
After multiplying (Z) by “96”, the value of “16 * X” may be added to calculate the reference address HADR (A) of the grid point “A” in the “C” component.

In step S49, the lattice points “A, X1, X2, H” in the triangular pyramid surrounding the transformation point P
(However, X1 and X2 are two of the grid points “B to G”.
In other words, two of the grid points “B to G” determined by the offset “X” in step S48 are sequentially read from the ROM 12. Specifically, the grid point “A, X” of the “C” component is sequentially incremented from the reference address HADR (A) of the grid point “A” in the “C” component calculated in step S48.
The grid point data of “1, X2, H” is sequentially read from the grid point data LUT shown in FIG.

In step S50, an interpolation operation at the conversion point P is performed. Specifically, the step S
Weight coefficient W (w1 to w4) read out at 46
Based on the grid point data of the grid points “A, X1, X2, H” in the “C” component read in step S49, the interpolation calculation at the conversion point P is performed by (Equation 47). Will be

In step S51, it is determined whether there is a next component. Specifically, the interpolation operation of the “M” component is performed when the interpolation operation of the “C” component is performed, and the interpolation operation of the “Y” component and the “Y” component is performed when the interpolation operation of the “M” component is performed. In this case, it is determined whether or not there is a “K” component.
If there is a next component, the process proceeds to step S52. On the other hand, when there is no next component, that is, when all “C,
When the interpolation calculation has been completed for the "M, Y, K" components, this processing ends.

In step S52, the reference address of grid point "A" in the next component is calculated. Specifically, as shown in FIG. 37, for the “C, M, Y, K” components, the grid points “A, B, D, H” and the grid points “A, C, G, H” , Grid points “A, E, F, H”, grid points “A, C, D, H”, grid points “A, E, G, H”, and grid points “A, B, F, H”. Since the grid point data is stored, “C” calculated in step S48 is used.
Address HADR of grid point "A" in the component
It is merely incremented sequentially from (A). Then, steps S49 to S52 are repeatedly executed, and the interpolation calculation of “M, Y, K” at the conversion point P is performed. That is, steps S49 to S52 are repeatedly executed, and “C, M, Y,
The interpolation operation of the “K” component is performed, and the RGB signals at the conversion point P are converted into CMYK signals. In general, since there are a large number of pixels to be converted, this process is repeatedly performed on all the read pixels.

As described in detail above, according to the sixth embodiment, the following operation and effect can be obtained in addition to the operation and effect of the fifth embodiment. (1) Also in the triangular pyramid interpolation, the interpolation calculation can be performed without determining whether or not the conversion point P corresponds to the exception processing. Therefore, unlike the second embodiment (the flowcharts shown in FIGS. 12 and 13), the same processing (the flowchart shown in FIG. 14) is performed regardless of whether the conversion point P corresponds to the exception processing. Weight coefficient W (w1 to w
8) and grid point data can be read. Therefore, even if the color conversion processing is performed by software,
Processing can be performed even faster. Moreover,
Even if the color conversion process is configured by hardware,
A simpler configuration can be achieved.

Each of the above embodiments can be modified and embodied as follows. Various data necessary for the interpolation calculation are stored in the ROM 12, but in order to read them out at high speed, the RAM 1
The processing may be performed by transferring the data to a third party or the like. When performing processing by transferring data to the RAM 13, R
Various data stored in the OM 12 may have the data structure shown in FIG. 3 and be transferred to the RAM 13 so as to have the data structure shown in FIG. The weight coefficient may be obtained by calculation and stored in the RAM 13 without storing it in the ROM 12.

In step S3 shown in FIG. 11, the readout of the weighting coefficient is performed during the processing of step S7 in the case of an MPU having an instruction for repeatedly performing the product-sum operation.
That is, in the process of step S7, the step is performed based on the reference address of the weighting factor calculated in step S2, the reference address of the grid point “A” in the “C” component calculated in step S5, and the number of product-sum operations. S2
The weighting factor is read from the reference address of the weighting factor calculated in the above, the grid point data is read out from the reference address of the grid point “A” in the “C” component calculated in step S5, multiplied, and each reference address is sequentially incremented. Then, the operation is repeated by the number of product-sum operations. The same applies to the flowcharts shown in FIGS. 12 and 13 and the flowchart shown in FIG.

In the above embodiments, the description has been made with reference to the grid point “A”, but other grid points “B to H”
It may be. In the fourth to sixth embodiments, only the grid point “A, H” is a grid point included in the six triangular pyramids. Point "H" is optimal.

In each embodiment, “C, M, Y,
Although the grid point data is stored in the order of the “K” component, the order may be any order regardless of this order. After the RGB signals are converted into the CMYK signals, the binarization processing or the dither processing may be continuously performed, and the recording unit 15 may record the signals on recording paper. As shown in FIG. 46, even in the case of triangular prism interpolation (six-point interpolation) using a triangular prism obtained by dividing a cube into two in the R = G plane,
The above embodiment may be applied.

As shown in FIG. 47, even in the case of quadrangular pyramid interpolation (five-point interpolation) using a quadrangular pyramid in which arbitrary five points are selected from eight vertices of a cube, the above embodiments can be applied. good. The color space conversion is not limited to the above embodiments, since there are some conversions such as Lab conversion and XYZ conversion other than conversion from RGB signals to CMYK signals.

Further, technical ideas other than the claims grasped from the above embodiments and the like will be described below together with their effects. [1] In an image processing apparatus for converting a color space, storage means for continuously storing grid point data and weighting factors of grid points surrounding a conversion point in the order necessary for calculation, and grid point data of grid points serving as references And a control for calculating reference addresses of weighting coefficients serving as references, sequentially incrementing the reference addresses, reading grid point data and weighting coefficients necessary for interpolation calculation of conversion points, and performing interpolation calculation of conversion points. Image processing apparatus comprising: With this configuration, color conversion processing can be performed at high speed using software.

[2] In the image processing apparatus according to any one of [1] to [3] and [1], the control means performs a binarization process or a dither process after converting the color space. An image processing device to be executed continuously. With this configuration, the value obtained by converting the color space can be recorded on a recording sheet by the recording unit without temporarily storing the value in a memory or the like. Therefore, a memory for storing the converted value is not required, and the reading operation and the recording operation can be collectively processed.

[3] The image processing apparatus according to [1] or [1], wherein the storage means stores a set of grid point data of grid points surrounding the conversion point. With this configuration, it is possible to reduce grid point data to be stored. Therefore, the storage capacity of the storage means can be reduced.

[4] The image processing apparatus according to claim 2, wherein the storage means stores any exceptional processing. With this configuration, it is possible to determine whether any of the exceptional processes is applicable.

[5] A recording medium provided in an image processing apparatus for converting a color space, in which grid point data and weighting factors of grid points surrounding a conversion point are successively stored in the order required for the calculation, and Calculates grid point data of grid points and reference addresses of reference weighting factors, and sequentially increments from these reference addresses to read grid point data and weighting factors necessary for interpolation calculation of conversion points, and perform conversion. A recording medium on which a program for causing a computer to execute a process of performing a point interpolation operation is recorded. With this configuration, it is possible to provide a program capable of performing color conversion processing at high speed.

[0302] In this specification, the term "recording medium" refers to any medium that can record a computer program, such as a readable semiconductor storage device, a magnetic storage device, and a magneto-optical storage device. It may be something. Specifically, it includes a semiconductor ROM, a floppy disk, a hard disk, an optical disk, a magneto-optical disk, a phase change disk, a magnetic tape, and the like.

[0303]

Since the present invention is configured as described above, it has the following effects. According to the first aspect of the present invention, color conversion processing can be performed at high speed using software.

According to the second aspect of the present invention, the first aspect
In addition to the effects of the invention described in (1), color conversion processing can be performed accurately without errors. According to the third aspect of the invention, in addition to the effects of the first aspect of the invention,
Higher speed can be achieved.

[Brief description of the drawings]

FIG. 1 is a circuit configuration diagram of a facsimile apparatus according to first to sixth embodiments.

FIG. 2 is an explanatory diagram for explaining lattice points in an RGB space.

FIG. 3 is an explanatory diagram for explaining an LUT of grid point data in cubic interpolation;

FIG. 4 is an explanatory diagram for explaining a cube surrounding a conversion point P in an RGB space.

FIG. 5 is an explanatory diagram for explaining an LUT of grid point data in cubic interpolation.

FIG. 6A is an explanatory diagram for explaining the principle of interpolation in cubic interpolation. (B) Explanatory drawing for explaining the weight coefficient in cubic interpolation.

FIG. 7 is an explanatory diagram for explaining an LUT of a weight coefficient in cubic interpolation.

FIG. 8 is an explanatory diagram for explaining a case where a conversion point P in the RGB space corresponds to exception processing.

FIG. 9 is an explanatory diagram for explaining an LUT for determining whether a conversion point P corresponds to exception processing.

FIG. 10 illustrates L of a weight coefficient including a case corresponding to exception processing.
FIG. 3 is an explanatory diagram for explaining a UT.

FIG. 11 is a flowchart showing an operation when performing color conversion processing in the first and fourth embodiments.

FIG. 12 is a flowchart showing an operation when performing color conversion processing in the second and fifth embodiments.

FIG. 13 is a flowchart showing an operation when performing color conversion processing in the second and fifth embodiments.

FIG. 14 is a flowchart illustrating an operation when performing color conversion processing in the third and sixth embodiments.

FIG. 15A is an explanatory diagram for explaining a method of dividing a cube into six. (B) Explanatory drawing for demonstrating the triangular pyramid obtained by dividing into six.

FIG. 16A is an explanatory diagram for explaining a triangular pyramid in a case where BL>GL> RL. (B) Explanatory drawing for demonstrating the triangular pyramid in case of GL>RL> BL. (C) Explanatory drawing for demonstrating the triangular pyramid in case of RL>BL> GL. (D) An explanatory diagram for explaining a triangular pyramid in the case of GL ≧ BL ≧ RL (RL ≠ GL). (E) Explanatory drawing for demonstrating the triangular pyramid in case of RL≥GL≥BL. (F) An explanatory diagram for explaining a triangular pyramid in the case of BL ≧ RL ≧ GL (GL ≠ BL).

FIG. 17 is an explanatory diagram for explaining a triangular pyramid in a case where BL>GL> RL.

FIG. 18A is an explanatory diagram for explaining the volume of the triangular pyramid Va in the case of BL>GL> RL. (B) Explanatory drawing for demonstrating the volume of the triangular pyramid Vb in case of BL>GL> RL. (C) Explanatory drawing for demonstrating the volume of the triangular pyramid Vc in case of BL>GL> RL. (D) Explanatory drawing for demonstrating the volume of the triangular pyramid Vd in case of BL>GL> RL.

FIG. 19A is an explanatory diagram for explaining the volume of the triangular pyramid Vc in the case of BL>GL> RL. (B) The side view which looked at the triangular pyramid Vc shown to (a) from the arrow direction.

FIG. 20 is an explanatory diagram for explaining a triangular pyramid in the case of GL>RL> BL.

FIG. 21A is an explanatory diagram for explaining the volume of the triangular pyramid Va in the case of GL>RL> BL. (B) Explanatory drawing for demonstrating the volume of the triangular pyramid Vb in case of GL>RL> BL. (C) Explanatory drawing for demonstrating the volume of the triangular pyramid Vc in case of GL>RL> BL. (D) Explanatory drawing for demonstrating the volume of the triangular pyramid Vd in case of GL>RL> BL.

FIG. 22 (a) is an explanatory diagram for explaining the volume of the triangular pyramid Vc when GL>RL> BL. (B) The side view which looked at the triangular pyramid Vc shown to (a) from the arrow direction.

FIG. 23 is an explanatory diagram for explaining a triangular pyramid in the case of RL>BL> GL.

24A is an explanatory diagram for explaining the volume of a triangular pyramid Va in the case of RL>BL> GL. FIG. (B) Explanatory drawing for demonstrating the volume of the triangular pyramid Vb in case of RL>BL> GL. (C) Explanatory drawing for demonstrating the volume of the triangular pyramid Vc in case of RL>BL> GL. (D) Explanatory drawing for demonstrating the volume of the triangular pyramid Vd in case of RL>BL> GL.

FIG. 25A is an explanatory diagram for explaining the volume of the triangular pyramid Vc in the case of RL>BL> GL. (B) The side view which looked at the triangular pyramid Vc shown to (a) from the arrow direction.

FIG. 26 is an explanatory diagram for explaining a triangular pyramid in the case of GL ≧ BL ≧ RL (RL ≠ GL).

FIG. 27 (a) is an explanatory diagram for explaining the volume of a triangular pyramid Va when GL ≧ BL ≧ RL (RL ≠ GL). (B) An explanatory diagram for explaining the volume of the triangular pyramid Vb when GL ≧ BL ≧ RL (RL ≧ GL). (C) Explanatory drawing for demonstrating the volume of the triangular pyramid Vc in case of GL≥BL≥RL (RL ≠ GL). (D) An explanatory diagram for explaining the volume of the triangular pyramid Vd when GL ≧ BL ≧ RL (RLＬGL).

FIG. 28 (a) is an explanatory diagram for explaining the volume of the triangular pyramid Vc when GL ≧ BL ≧ RL (RL ≠ GL). (B) The side view which looked at the triangular pyramid Vc shown to (a) from the arrow direction.

FIG. 29 is an explanatory diagram for explaining a triangular pyramid when RL ≧ GL ≧ BL.

FIG. 30 (a) is an explanatory diagram for explaining the volume of a triangular pyramid Va when RL ≧ GL ≧ BL. (B) An explanatory diagram for explaining the volume of the triangular pyramid Vb when RL ≧ GL ≧ BL. (C) Explanatory drawing for demonstrating the volume of the triangular pyramid Vc in case of RL≥GL≥BL. (D) Explanatory drawing for demonstrating the volume of the triangular pyramid Vd in case of RL≥GL≥BL.

FIG. 31A is an explanatory diagram for explaining the volume of the triangular pyramid Vc when RL ≧ GL ≧ BL. (B) The side view which looked at the triangular pyramid Vc shown to (a) from the arrow direction.

FIG. 32 is an explanatory diagram for explaining a triangular pyramid in a case where BL ≧ RL ≧ GL (GL ≠ BL).

FIG. 33 (a) is an explanatory diagram for explaining the volume of a triangular pyramid Va when BL ≧ RL ≧ GL (GL ≠ BL). (B) An explanatory diagram for explaining the volume of the triangular pyramid Vb when BL ≧ RL ≧ GL (GL ≠ BL). (C) Explanatory drawing for demonstrating the volume of the triangular pyramid Vc in case of BL ≧ RL ≧ GL (GL ≠ BL). (D) An explanatory diagram for explaining the volume of the triangular pyramid Vd when BL ≧ RL ≧ GL (GL ≠ BL).

FIG. 34 (a) is an explanatory diagram for explaining the volume of the triangular pyramid Vc when BL ≧ RL ≧ GL (GL ≠ BL). (B) The side view which looked at the triangular pyramid Vc shown to (a) from the arrow direction.

FIG. 35 is an explanatory diagram for explaining an LUT of a weight coefficient in triangular pyramid interpolation.

FIG. 36 is an explanatory diagram for explaining an LUT that stores an offset determined based on the magnitude relationship of each value of (RL, GL, BL).

FIG. 37 is an explanatory diagram for explaining an LUT of grid point data in triangular pyramid interpolation.

FIG. 38 is an explanatory diagram for explaining an LUT of grid point data in triangular pyramid interpolation.

FIG. 39 is an explanatory diagram for explaining a triangular pyramid when RH = 15, GH <15, and BH <15, and when RL ≧ GL ≧ BL.

FIG. 40 (a) RH = 15, GH <15, BH <15
FIG. 4 is an explanatory diagram for explaining the volume of the triangular pyramid Va in the case of RL ≧ GL ≧ BL. (B) Triangular pyramid V when RH = 15, GH <15, BH <15, and when RL ≧ GL ≧ BL
Explanatory drawing for demonstrating the volume of b. (C) Triangular pyramid V when RH = 15, GH <15, BH <15, and when RL ≧ GL ≧ BL
FIG. 4 is an explanatory diagram for explaining the volume of c. (D) Triangular pyramid V when RH = 15, GH <15, BH <15, and RL ≧ GL ≧ BL
FIG. 4 is an explanatory diagram for explaining the volume of d.

FIG. 41 (a) RH = 15, GH <15, BH <15
FIG. 9 is an explanatory diagram for explaining the volume of the triangular pyramid Vc in the case of RL ≧ GL ≧ BL. (B) The side view which looked at the triangular pyramid Vc shown to (a) from the arrow direction.

FIG. 42 is an explanatory diagram for explaining a triangular pyramid when RH <15, GH = 15, BH = 15, and when RL>BL> GL.

FIG. 43 (a) RH <15, GH = 15, BH = 15
FIG. 4 is an explanatory diagram for explaining the volume of the triangular pyramid Va in the case of RL>BL> GL. (B) Triangular pyramid V when RH <15, GH = 15, BH = 15, and when RL>BL> GL
Explanatory drawing for demonstrating the volume of b. (C) Triangular pyramid V when RH <15, GH = 15, BH = 15, and when RL>BL> GL
FIG. 4 is an explanatory diagram for explaining the volume of c. (D) Triangular pyramid V when RH <15, GH = 15, BH = 15, and when RL>BL> GL
FIG. 4 is an explanatory diagram for explaining the volume of d.

FIG. 44 (a) RH <15, GH = 15, BH = 15
FIG. 9 is an explanatory diagram for explaining the volume of the triangular pyramid Vc in the case of RL>BL> GL in the case of FIG. (B) The side view which looked at the triangular pyramid Vc shown to (a) from the arrow direction.

[FIG. 45] L of weight coefficient including a case corresponding to exception processing
FIG. 3 is an explanatory diagram for explaining a UT.

FIG. 46 is an explanatory diagram showing an example of triangular prism interpolation (six-point interpolation) as another embodiment.

FIG. 47 is an explanatory diagram showing an example of quadrangular pyramid interpolation (5-point interpolation) as another embodiment.

[Explanation of symbols]

DESCRIPTION OF SYMBOLS 1 ... Facsimile machine as an image processing apparatus, 11 ... MPU which comprises control means, 12 ... ROM which comprises storage means and control means, 13 ... RAM which comprises control means.

 ──────────────────────────────────────────────────続 き Continued on the front page F term (reference) 2H030 AD12 BB02 5B057 CA01 CB01 CE18 CH07 CH11 CH18 5C077 LL18 MP08 PP32 PP33 PQ08 PQ23 RR19 5C079 HB01 HB03 HB12 LA28 LA31 MA04 NA11 PA01

Claims (3)

[Claims] 1. An image processing apparatus for converting a color space, comprising: storage means for continuously storing at least grid point data of grid points surrounding a conversion point in an order necessary for calculation; and grid point data at a grid point serving as a reference. And a control means for calculating the reference address, sequentially incrementing the reference address, reading grid point data necessary for the interpolation operation of the conversion point, and performing the interpolation operation of the conversion point. 2. The image processing apparatus according to claim 1, wherein the storage unit stores whether or not the exception processing is performed.
An image processing apparatus wherein the control means performs an interpolation calculation of a conversion point depending on whether or not the exception processing is performed. 3. The image processing apparatus according to claim 1, wherein the control unit performs an interpolation operation of the conversion point without determining whether the exception processing is performed.