JPH01134681A - System for converting color picture data - Google Patents

Abstract

PURPOSE:To attain the structure conversion, color conversion or brightness conversion of encoded color picture data as they are by providing respective working means to add a work processing to respective quantized structure information, brightness information and color information. CONSTITUTION:The output signal 316 of the quantized brightness information, structure information and color information is converted to a parallel signal from an MUX through a transmission path 320 and a DMUX. Brightness information (L) 308 is inputted to a brightness converting part 322, brightness- converted in correspondence to control quantity 323 and outputted through an orthogonal inverse transformer 325, R, G and B decoders 333, 335 and 337. On the other hand, color information (C) 314 are converted by a color data converter 100 in correspondence to color conversion control quantity 101 and outputted through decoders 328 and 329 and the R, G and B decoders 333, 335 and 337. Structure information (S) 310 are inputted to an S data converter 200, structure-converted and outputted through a decoder 326, the orthogonal transformer 325 and Y, M and C decoders 333', 335' and 337'.

Description

[Detailed Description of the Invention] [Field of Industrial Application] The present invention relates to a color image data conversion method, and particularly to a color image data conversion method that performs structural transformation such as rotation on encoded color image data. .

[Prior Art] Conventionally, when transmitting or storing images, it has been common to compress and suppress redundancy through encoding in consideration of efficiency. Not only black-and-white and binary images, but also color images and the like have a huge amount of information, and their encoding is essential.

In particular, in the case of color images, since the amount of information is large, it is desired to realize an efficient encoding method.

On the other hand, fax and electronic files.

In a copying machine or the like, there are cases where it is necessary to perform structural conversion, brightness conversion, single color conversion, etc. on data transmitted or stored in a buffer or the like.

In such cases, it is efficient and desirable to convert the encoded data as it is. However, with conventional encoding methods, it has not been possible to directly convert encoded color image data.

Conventionally, when such a need arises, in facsimiles and the like, the receiving side transmits information regarding the conversion from the receiving side to the sending side, and the sending side converts the information and resends it. Therefore, in this case, as a matter of course, it takes a lot of time and the content of mutual communication becomes complicated. In addition, since the above methods cannot be used for electronic files, it is necessary to first decode the encoded data and then convert the decoded data, which may cause deterioration in image quality due to repeated processing. , the advantages of handling encoded data due to the need for working memory, etc., were not utilized.

[Problems to be Solved by the Invention] The present invention has been proposed in order to eliminate the drawbacks of the above-mentioned conventional examples. The purpose of this invention is to propose a color image data conversion method that performs color image data conversion.

[Means for Solving the Problems] The configuration of the present invention for achieving the above-mentioned problems includes a dividing means for dividing color image data into blocks, brightness information related to brightness from the blocks, and a method for dividing color image data into blocks. an extracting means for extracting structural information related to the color and color information related to the color; a quantizing means for quantizing the extracted lightness information, structural information and color information; and among these quantized information, and processing means for applying processing to the structural information.

Further, a dividing means for dividing color image data into blocks, an extraction means for extracting brightness information related to brightness, structural information related to structure, and color information related to color from the blocks, and the extraction means quantization means for quantizing the brightness information, structure information, and color information; processing means for processing the structure information among these quantized information; and second processing means for applying processing to the information or color information.

[Operation] In the above configuration, when the processing means performs structural transformation,
All you need to do is convert and process only the structural information. Furthermore, when converting the brightness, only the brightness information needs to be converted, and when converting the color, only the color information needs to be converted and processed.

[Examples] Examples according to the present invention will be described in detail below with reference to the accompanying drawings.

<Principle of Embodiment> Color information based on the RGB color system has a property that since there is a strong correlation between RGB signals, a large amount of information will be missing if each of R, G, and B is compressed and encoded individually. Therefore, the RGB signal system is not suitable for compression encoding. Therefore, in this embodiment, the color image data of the RGB three primary color system is converted to a color system with less inter-im correlation, and the color image data of this new color system is cut into small blocks. Then, as shown in FIG. 2(a), each block is compressed and encoded.

In FIG. 2(a), L represents brightness information regarding the brightness within the block, S represents structural information regarding structures such as edges within the block, and C represents color information regarding the color within the block. In this way, highly efficient compression encoding is achieved by extracting and encoding brightness information, structural information, and single-color information from color image data in the RGB color system.

Furthermore, when converting color image data that has been encoded as described above, for example, when converting only the structure, it is only necessary to convert only the structure information part as shown in Figure 2 (b), and the brightness If you want to convert only the brightness information part as shown in Figure 3, you only need to convert the brightness information part, and if you want to convert the color, you only need to convert the color information part as shown in Figure 4. This eliminates the drawbacks of the conventional method.

Now, as a color system with little correlation between signals, in the embodiment described below, L"a"b of CIE1976 uniform color space is used.
``Adopt a color system.

<Conversion to RGB4L"a"b"> Figure 5 (a)
~(C) is the RGB system in the target image → L″a* b
*It shows the conversion to the system and the cutting out of 4×4 blocks. 201 is a manuscript, and 'A' is included in the manuscript 201.
The letter J is drawn on it. Blocks 202 are cut out in 4×4 size starting from the corner of the document.

203 is one of the blocks extending over the character "Aj," indicating a case where an edge portion is included.

FIG. 5(b) shows the distribution of color image data of the block 203 by RGB, and particularly shows the case where the characters of the block 203 are red characters. In that case, the three primary colors of RGB are as shown in the figure, and edges appear only in R. Figure 5 (C)
converts the RGB signals shown in Figure 5(b) to L"a'b"
This shows the case when converted to . In the figure, L, -L, etc. indicate the L' acid component in the block. Incidentally, the subscripts such as ~1 represent 10 to 15 for convenience.

Here, a conversion formula for converting from RGB to "a" and "b" signals is shown below.

X =X r R+ X g G + X b BY
=Y, R+Y, G+Yb BZ=Z
r R+ Z t G + Z b B However, X r
,x,,xb+Yr,y,,yb,Zb, etc. are constants.

From this, L” = 116・(Y/ Y o) l/3
++ 16a' = 50(1(X/Xo)"'
(y/Yov/3b” = 2001Y/Y
o)”3(Z / Z oν′3However, xo, yo, Z
o is the value of the reference white light, Y/Y o > 0.
008856.

(Compression encoding of L'') It has been mentioned that the L''a'b'' system has little correlation between signals.The encoding shown in Figure 2 from this L''a''b'' system requires orthogonal transformation, Especially the Hadamard transformation.

Discrete CO5 conversion is suitable. That is, since L'' includes structural information in addition to brightness information, by performing the above orthogonal transformation, the brightness information component and the structural information component are extracted from L''. In the following embodiments, a second-order Hadamard transform among these orthogonal transforms is used. -Numerical second-order Hada
The mard transformation is (F) = (1/m-n) ”2
It is expressed as (H) (L) (H"). Here, (L): mxn original matrix (H): Hadamard matrix (H")
: Transposed matrix of (H) (F) : Matrix after transformation of rr, xn.

Here, if (L) is Ll of the above-mentioned L"a'b'" system, then (F) is the image obtained by Iadamard transformation from (L), from which brightness information and structure information have been extracted. It will represent the data. In this case, it is (1/mn) l/2 to 4. Also, for convenience, if (L) and (F) are expressed in vector representation, the above equation becomes: F plate = (1/4) Σ HIjLj However,
i=o~15 (i.e. ~2), and HIJ is 16 x
16 represents the Hadamard matrix.

Therefore, the above formula becomes. Note that + in the Hadamard matrix represents 1, and - represents -1.

As can be seen from the above formula, F. is the average brightness within the block,
That is, it represents the brightness information of the block.

Further, Fl (i=1 to F) other than F0 represents structural information such as edges included in the plot.

<Embodiment of Encoding Circuit> FIG. 1 shows an embodiment of encoding according to the present invention. 3
01 is a 4-line buffer that temporarily stores input RGB signals for block extraction. That is, blocks are cut out by reading out signals for four lines that have been stored in a size of 4×4. 302 is RGB
-+L"a"b" conversion circuit, which is converted based on the conversion formula shown earlier. A specific example of this is shown in the sixth section.
This is the circuit shown in the figure, and the conversion is 401°402.40 in Fig.6.
This can be realized using the look-up table method described in No. 3.

303 is the L" output from the L"a"b" converting unit 302, and is the block shown in FIG. 5(C).
The signals are output in the order of +..., L, and so on.

304 in FIG. 1 is an orthogonal transform unit, and t
A specific circuit for performing l a d a [O a r d conversion is shown in FIG. In FIG. 7, 410 is a Ha that generates addresses in the row direction when performing matrix operations.
This is a daird matrix address generator, and in order to perform the above matrix operation, it is HI in synchronization with the input Ll.
Output J. 411 etc. is 11 a da a to human power Ll
This is a look-up table (LUT) that multiplies the coefficients of the m a r d matrix and outputs the result. In order to perform the above matrix operation, when the Hadamard matrix address generator 410 addresses the look-up table in synchronization with the input Ll. , in the lookup table, H
The adamard coefficient is output, and Ll and 11
Multiplication is performed by the ad a m a r d coefficient.

412 is an adder that performs cumulative addition; for example, adder 4
11, Lo +LljL2 +=+LP is calculated. 413 is a 1/4 divider.

Below, 415 to 418 are the same, and there are a total of 16 sets. That is, it exists for each F, and the following operations are executed.

FO = 1/4 (Lo +t,, +t, 2+...
+LF) Fr = 1/4 (Lo Ll-L2+・
...+LF) In Figure 1, 305 is F in this output. As mentioned above, this is a coefficient representing the brightness of the block. 307 is a quantizer that quantizes this, and Fo
The 10 bits of the image are quantized to 8 bits to obtain brightness information) 3
Outputs 08.

306 is a coefficient of F1 to F'' other than F0, and as described above, this is a coefficient representing the structure of the etch included in the block, and is encoded into 12 bits by the quantizer 309. That is, the structure The information (S) is rounded into 4096 predetermined patterns.

Reference numerals 311 and 312 in FIG. 1 denote averaging circuits for taking block averages of a'' and b'', respectively, which are the outputs of the L'a''l)'' converter 302, and are composed of an adder and a divider. 313 is a quantizer that collectively quantizes the block average values of a″b′, and quantizes the 12-bit color information (C).
Quantize to

Incidentally, it is known that all of the quantizers 307, 309, and 313 are generally efficient if they are configured as vector quantizers.

315 in FIG. 1 is the brightness information (L) 3 explained so far.
08. This is a multi-blephr that combines structure information (S) 310 and color information (C) 314 into one code. 316 is the output signal thereof, that is, the encoded code shown in FIG. 2(a). This will be sent to the transmission line or accumulator. The color image data encoded in this manner is highly efficiently compressed, and at the same time exhibits its advantages, such as the ease of data conversion described below.

<Data conversion = decoding> As explained in relation to FIG. 2(b), FIG. 3, and FIG. 4, the color image data encoded as shown in FIG. 2(a) undergoes structural transformation. , convenient for brightness conversion or color conversion.

First, brightness conversion will be explained.

Brightness Conversion> In FIG. 8, 320 is a transmission line or an accumulator, and 321 is a DMUX that performs an operation opposite to that of the multiplexer 315. That is, serial brightness information, structure information, etc. are converted into parallel information. 322 is a conversion unit that performs brightness conversion; brightness conversion unit 322
The manual input 323 is for inputting the degree of brightness conversion, which is an 8-bit control amount. Figure 10 shows the brightness conversion section 32.
An example of a circuit when 2 is configured with a look-up table (LUT) is shown below. When this brightness conversion is performed, L to L'
becomes. FIG. 11 shows an example of the 8-bit brightness conversion amount 323, and the range of possible values in this case is 0 to 255. The brightness can be changed to 256 levels in total, and 128 is the default value with no change.

Reference numeral 325 in FIG. 8 is an orthogonal inverse transformer, which can be configured with the same hardware as the orthogonal transformer 304 in FIG. 1 used for encoding. Further, 326 is for decoding the structure information (S), 3
27 is its output, 328 and 329 are each for a'b'' decoding, and 33o.

331.332 are each decoded Lll aIl b-
333, 335, 337 are R', G' respectively.
, B' for decoding, 334, 336° and 338 are output lines of decoded R', G', and B'. In this way, the brightness conversion is easily performed.

Color conversion〉 Figure 11 shows the data format of color information (C).
Color information (C) is the hue (θ) in a*b* space.
and saturation (h). The relationship between hue and saturation θ is as shown in FIG. 12(a). FIG. 12(C) shows the state of division on the a"-b" space, with 50
Each grid point as indicated by 1 is selected as a representative color by the quantization circuit 313 in FIG.

FIG. 13 shows an embodiment of a conversion/decoding circuit that performs color conversion and decoding. The circuit that differs from the brightness conversion circuit shown in FIG.
00 is provided. A quantity instructing how to convert color data is input to the color data converting section 100 via a color conversion amount control line 101. The color information after color conversion becomes C'. FIG. 14 shows an example of a circuit in which the color data converter 100 is configured with a look-up table.

Next, the color conversion method is performed as shown in FIGS. 15(a) and 15(b). The conversion amount data is internally divided into 8 bits, with the upper 4 bits giving the hue θ and the lower 4 bits giving the amount of change in saturation.

<Structural Conversion> Figure 16 shows an example of a circuit for structural conversion. In addition, Fig. 8, 1st
The same reference numbers as in Figure 3 serve the same function. In FIG. 16, 320 is a transmission path or an accumulator, and 321 is a DMUX that performs the opposite action to that of the multiplexer 315. That is, serial color information, brightness information, structure information, etc. are converted into parallel information. 200 is a structure conversion unit (hereinafter referred to as S data conversion unit) that performs structural conversion;
23 is for inputting whether or not there is structural conversion.

FIG. 17 shows an example of a circuit in which the S data conversion section 200 is configured with a look-up table (LUT). When this structural conversion is performed, S becomes S'. Reference numeral 339 denotes an address management section of a buffer memory section for at least one screen provided in a transmission line or an accumulator.

As an example of structural transformation, a 90° rotation method using Hadamard transformation characteristics will be described below. FIG. 18 shows a 90° rotation.

This will be explained with reference to FIGS. 19(a), (b) and FIG. 20.

Figures 11(a) and (b) are examples of original data X and data Y after Hadamard transformation. ) is X. On the other hand, (a) and (b) of data Y after Hadamard transformation
The relationship is a mirror image with respect to the A' axis. That is,
Regarding the structural information in FIG. 3(a), if the code of the data in the A'-axis mirror image of the unconverted information is replaced as the converted information, it becomes possible to rotate the image by 90 degrees.

FIG. 20 shows this situation.

In the figure, a is the original image, FIG. 19(a).

The image obtained by the process described in (b) is b,
It is a mirror image of a. However, the direction indicated by the arrow in the figure is the scanning direction, which is different from the direction in which data is written to the transmission path or the storage device 320 (writing is in the horizontal direction).The buffer memory address management unit operates this direction. 33
It is 9.

The mirror image obtained in this manner is corrected to an image in the correct position by reversing the writing/reading direction of the buffer memory (line memory or page memory) when outputting to the printer.

That is, the image data read out in the direction of the arrow shown at C in FIG. 20 is printed in the direction of the arrow shown at d in the printer.

Reference numeral 325 in FIG. 16 is an orthogonal inverse transformer, which can be configured with the same hardware as the orthogonal transformer 304 in FIG. 1 used for encoding. Also, 326 is for decoding the structure information (S),
327 is its output, 328 and 329 are each for a″b1 decoding, and 33o.

331 and 332 are respectively decoded L"a"b0b0 signals, 333', 335' and 337' are 334' and 336" for Y, M and C decoding, respectively.

338' is decoded Y (yellow) 1M (magenta)
, C (cyan) output line. In this way,
Structural transformations are easily performed.

In the embodiments described above, L"a"b' is used, but L"u'v" or NTSC YIQ
, PAL, YUV, etc. are also applicable.

Further, although the orthogonal transformation is shown as Hadamard transformation, it is also possible to use discrete COS transformation, slant transformation, or the like.

Further, although the quantizer is described as vector quantization, there is no particular limitation. Note that the bit allocation of the brightness information, structure information S1, and color information C is not limited to that shown in the above embodiment.

In addition, the input signal is not limited to RGB, but depending on the sensor, YG
An input such as C may also be considered.

Further, in FIG. 1, a"b" is represented by an average value, but it may be stored in more detail. In addition, in the examples, C(
Although the color information is expressed in terms of hue and saturation, it is not limited to this.

In this embodiment, an example of conversion at the time of decoding is shown, but as shown in FIG. 21, there is a method of decoding before decoding, that is, after conversion in the storage section, or a method of decoding after conversion as shown in FIG. 22, after encoding. There is also a method of storing it or outputting it to a transmission section.

[Effects of invention As explained above, according to the present invention, brightness.

Color image data that has been separated and encoded into elements representing each of the eight structural chromaticities can be converted and processed not only for the structural information but also for the lightness information and chromaticity information, while remaining as encoded data.

[Brief explanation of the drawing]

FIG. 1 is a block diagram of an encoding circuit according to an embodiment of the present invention, FIG. 2(a) is a diagram showing the structure of color image data encoded by the encoding of this embodiment, ) is a diagram showing the data processing part in structural conversion, Figures 3 and 4 are respectively in brightness conversion and two-color conversion,
FIG. 5(a) is a diagram showing an example of color image data in the example. FIGS. Figure 6 is a block diagram of the L'a'b' conversion section, Figure 7 is a block diagram of the orthogonal transformation section, and Figures 8 and 9 are the brightness conversion. Fig. 10 is a diagram showing an example of brightness conversion, Fig. 11 is a diagram showing the structure of color information C, and Fig. 12 (a) and (b) are diagrams showing the configuration of color information C. , a diagram showing the relationship between hue θ and saturation, Figures 13 and 14 are circuit diagrams of an embodiment that performs color conversion and decoding, and Figures 15 (a) and (b) are color data conversion Fig. 16 and Fig. 17 are circuit diagrams for performing structural conversion and decoding, Fig. 18 is a diagram showing one of the structural conversions, 90° rotation, and Fig. 19. (a) and (b) are explanatory diagrams of symmetry by Hadamard transformation, Figure 20 is a diagram showing a series of processing, and Figures 21 and 22 are other examples of structural transformation. In the figure, 100 . . . Color data conversion section, 200 . . . S data conversion section, 302 . . . L"a'b" conversion section, 304
...Orthogonal transformation section, 307, 309, 313... quantization section, 311...a" averaging section, 312...b" averaging section, 315...MUX, 320... transmission line or Accumulator, 321...DMUX, 322...L data conversion section, 325...Orthogonal inverse transformation section, 326...Y decoding L
UT, 328・“a” decoding LUT, 329・b” decoding LUT, 333...R decoding LUT, 333'...Y
Decoding LUT, 335...G decoding LUT. 335'...M decoding LUT, 337...B decoding LU
T, 337'-C decoding LUT, 339...Buffer memory address management section.

Claims (7)

[Claims] (1) dividing means for dividing color image data into blocks; extraction means for extracting brightness information related to brightness, structural information related to structure, and color information related to color from the blocks; Color image data characterized by comprising: quantization means for quantizing the extracted brightness information, structure information, and color information; and processing means for processing the structure information among these quantized information. Conversion method. (2) The color image data conversion method according to claim 1, wherein the processing means performs the processing using codes representing a structure after encoding. (3) The color image data conversion method according to claim 1, wherein the processing means utilizes symmetry of an orthogonal transformation matrix. (4) The color image data conversion method according to claim 1, wherein the color image data is represented by a signal system with weak inter-signal correlation. (5) The color image data encoding method according to claim 4, wherein the color image data is expressed as L^*a^*b^*. (6) The color image according to claim 1, wherein the extraction means includes orthogonal transformation means and performs orthogonal transformation on brightness components within the block to extract the brightness information and structure information. Data conversion method. (7) a dividing means for dividing color image data into blocks; an extracting means for extracting brightness information related to brightness, structural information related to structure, and color information related to color from the blocks; quantization means for quantizing the extracted brightness information, structure information, and color information; processing means for processing the structure information among these quantized information; A color image data conversion method comprising: second processing means for applying processing to brightness information or color information.