JPH0823510A - Interpolation circuit for television signal - Google Patents

Abstract

PURPOSE:To eliminate the need of providing a memory for interpolation data and to miniaturize a circuit scale. CONSTITUTION:This circuit is provided with two line buffer memories 10a and 10b for respectively storing the line data of the source signals of one field, an input control circuit 6 for outputting the same line data twice and supplying them to the memories 10a and 10b and a shift register 13, an arithmetic interpolation circuit 14 and an interpolation value register 15 for performing arithmetic interpolation by using 7X2 or 3X2 pieces of pixel data taken out from the memories 10a and 10b. The obtained interpolation data are subscribed in the part where the data required for the arithmetic interpolation are stored of the memories 10a and 10b.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a television signal interpolation circuit for generating a one-frame television signal from a one-field television signal.

[0002]

2. Description of the Related Art Conventionally, in a video printer for obtaining a hard copy of a television image, for example, when an image of one frame is printed, there is a problem that the obtained image is blurred due to interlaced scanning.

Therefore, a frame image is artificially generated from one field of a television signal and the frame image is printed. As described above, in order to form the pseudo frame signal from the field signal, it is necessary to generate the missing information by interpolation.

As a method of interpolation for forming a pseudo frame signal from such a field signal, for example, the data of one line before is used as it is as an interpolation value, or the average value of upper and lower pixels is interpolated. There are a method of treating as an value and a method of calculating an interpolated value by recognizing patterns of three pixels above and below the pixel position to be interpolated.

[0005]

Here, in the method of directly using the data one line before as the interpolation value,
Although a circuit for realizing the method for obtaining the interpolation value can be configured very easily, it is the worst of the three interpolation methods in terms of gradation, resolution, jerkiness, etc., and the image quality is not good.

The method of treating the average value of the upper and lower pixels as the interpolated value can be realized relatively easily in terms of circuit,
Gradation is also improved, but problems still remain in terms of resolution and jerkiness.

In the method of calculating the interpolated value by pattern recognition of the upper and lower three pixels of the last interpolated pixel, the circuit scale can be realized in a medium scale, and in terms of gradation and jerkiness, there are two other factors.
There are improvements over the two methods. However, even this method is not sufficient in terms of diagonal resolution and jerkiness, for example. Further, in this method, since the pattern recognition area is small, a pattern recognition error may occur. When the pattern recognition error occurs, a noise-like portion may be found in the interpolated image. There is. Further, it is possible to develop this method to recognize a pattern from three or more pixels above and below. However, if the number of pixels for pattern recognition is increased, the circuit scale increases exponentially, which is not practical. I'm missing.

Further, the conventional interpolating circuit requires a line buffer memory for performing an interpolating operation and a memory for storing the obtained interpolating data, which also causes a large circuit scale. It is one.

Therefore, the present invention has been made in view of the above-mentioned circumstances, and it is not necessary to increase the circuit scale, and further, for example, even in the case of an oblique image, the gradation, resolution, and jerkiness are taken into consideration. It is an object of the present invention to provide a television signal interpolation circuit capable of obtaining a sufficient interpolation image.

[0010]

The present invention has been made in view of the above circumstances, and an interpolating circuit for a television signal of the present invention is a signal of one frame from an original signal of one field of the television signal. W that stores the line data of the original signal of one field, respectively.
Number of line buffers (w is 2 or more), line data supply means for outputting the same line data v times to the w number of line buffers, and a predetermined area stored in each of the w number of line buffers. Interpolation calculation means for performing interpolation calculation using data, and the interpolation data by the interpolation calculation means is overwritten on the portion of the w line buffers in which the data after the interpolation calculation is stored. It is what

[0011]

According to the present invention, the interpolation data by the interpolation calculation means is overwritten on the portion of the w line buffers in which the data for which the interpolation calculation is completed is stored. Therefore, a separate memory for the interpolation data is used. Need not be provided.

[0012]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENT A preferred embodiment of the present invention will be described below with reference to the drawings.

As shown in FIG. 1, the television signal interpolating circuit of the embodiment of the present invention generates one frame signal from an original signal of one field of the television signal. The line buffer memories 10a and 10b, which store w line data respectively (w is 2 or more and are two in the example of FIG. 1), and the same line data are output v times (twice in this embodiment), are output as described above. The input control circuit 6 as the line data supply means for supplying the line buffer memories 10a and 10b, and the predetermined areas stored in the line buffer memories 10a and 10b (in this embodiment, a 7 × 2 pixel area or A shift register 13 and an interpolation calculation circuit 14 as interpolation calculation means for performing an interpolation calculation using pixel data of (3 × 2 pixel area),
An interpolation value register 15 is provided, and the interpolation data obtained by the interpolation calculation means is stored in the line buffer memories 10a and 10a.
This is to overwrite the portion in which the data for which the interpolation calculation of b is completed (that is, the data that is no longer necessary for the interpolation calculation) is stored.

In FIG. 1, the interpolation circuit of this embodiment is applied to a video printer for obtaining a hard copy of a television image, for example, and therefore a print data write clock is supplied to the terminal 1. , 8 bits of image data, that is, print data from the frame memory, is input to the terminal 3, and a head active signal which is a signal indicating each color printing state is input to the terminal 4.
Is supplied with a print timing pulse. Also, terminal 2
Outputs a print data request signal for the frame memory. Of these terminals 1-5, terminals 1, 2,
Reference numeral 3 is connected to an input control circuit 6 via a frame memory (not shown) and an interface circuit, and terminals 4 and 5 are connected to a CPU (central processing unit) and an interface circuit (not shown). It A field memory may be used instead of the frame memory.

The input control circuit 6 controls the fetching of data from the frame memory to the line buffer memories 10a and 10b of the next stage.

Each of the memories 10a and 10b is a one-line buffer memory for holding image data, which is print data supplied to the terminal 3 via the input control circuit 6, and is, for example, a static RAM (SRA).
M).

The work table transfer control circuit 9 fetches data from the memories 10a and 10b. That is, the work table transfer control circuit 9
Is a circuit for performing address control for fetching image data required for interpolation calculation described later from the memories 10a and 10b. The work table transfer control circuit 9 takes out necessary data (7 × 2 pixel data in the case of the present embodiment) from the memories 10a and 10b and transfers it to a work table composed of a shift register 13, for example.

Shift register 13 of the work table
Of the image data transferred to, the pixel data necessary for the interpolation calculation described later are sent to the interpolation calculation circuit 14, where the pattern recognition using the image data is performed and the interpolation calculation for calculating the interpolation value is performed. To do.

The interpolation value obtained by the interpolation calculation circuit 14 is temporarily held in the interpolation value register 15. That is, since the interpolation value register 15 uses the past interpolation pixel as data when performing the interpolation calculation of the next pixel, it is a data register for temporarily holding the data of the past interpolation pixel.

The interpolated pixel data held in the interpolated value register 15 is overwritten in the storage area of the memory 10a or 10b where the interpolated pixel data is stored for the reason described below. It

After that, the pixel data used for the interpolation calculation and the data of the overwritten interpolation pixel are sequentially read from the memories 10a and 10b and sent to the transfer control circuit 7. The transfer control circuit 7 controls the timing at which data is transferred to the structure for printing of the next stage via the terminal 8.

Here, the above-mentioned frame is controlled by the input control circuit 6.
Read from the memory and sent to the memories 10a and 10b.
The arrangement of the data on the input line is as follows.
It Note that i shown below is the i-th line of the field image.
Is shown. Also, A_j, B_j, C_j, D _j・ ・ ・ ・ ・ ・, X_j, Y_j, Z_j
Is each pixel value in any one line of the field image
Is shown.

Image line data of input line field signal ······· nth line A _i-1 B _i-1 C _i-1 D _i-1 ... X _i-1 Y _i-1 Z _i-1 nth line A _i-1 B _i-1 C _i-1 D _i-1 ... X _i-1 Y _i-1 Z _i-1 nth line A _i B _i C _i D _i・ ・ ・ X _i Y _i Z _i nth line A _i B _i C _i D _i・ ・ ・ X _i Y _i Z _i n + 2 line A _{i + 1} B _{i + 1} C _{i + 1} D _{i + 1} ...・ X _{i + 1} Y _{i + 1} Z _{i +} 1th n + 3 line A _{i + 1} B _{i + 1} C _{i + 1} D _{i + 1} ... X _{i + 1} Y _{i + 1} Z _{i + 1} ...・ ・ ・

That is, for example, the above memories 10a, 10
When the (n-2) th line is input as an input line to one of the memories b, the n-1th line, which is the same data, is subsequently input to the other memory. Similarly, when the data of the nth line is input to one memory, the same data of the (n + 1) th line is input to the other memory, and when the n + 2th data is input to one memory, the other memory is input. In order that the data of the (n + 3) th line which is the same data is input to the memory 10a,
The same image data is input to 10b.

In the circuit of this embodiment, the memory 1
For 0a or 10b, one of the held input image data of the same two lines is rewritten to the interpolated data, and the interpolated data and the unrewritten image data are sequentially output. I am trying.

For example, the data of the (n-1) th line is already held in the memory 10a,
It is assumed that the data of the nth line is transferred to b.

When the image data of the n-th line is input to the memory 10b, and the number of data equal to or more than the number of data for which interpolation calculation can be performed begins to be stored in the memory 10b, the work table transfer control circuit 9 supplies the data required for the calculation to the memory 10a. 10b to the work table shift register 13.

[0028] That is, the shift register 13 consists of two shift registers 13a and 13b, the n-1 pixel data registers a _m line from the memory 10a on one of the shift register 13a, a _{m + 1} , A _{m + 2} , a
_{m + 3, a m + 4} , a m + 5, a m + 6 are stored are shifted sequentially to the other shift register 13b the n-th pixel data registers b _m of the line from the memory 10b to, b
_The data are sequentially shifted and stored in _{m + 1} , b _{m + 2} , b _{m + 3} , b _{m + 4} , b _{m + 5} , b _{m + 6} .

When a predetermined number of pixel data of the (n-1) th line and the nth line are prepared in the shift register 13, each pixel data is output from the shift register 13 and sent to the interpolation calculation circuit 14.

The interpolation calculation circuit 14 performs pattern recognition, which will be described later, by using the supplied pixel data of the (n-1) th line and the nth line, and the line between the (n-1) th line and the nth line. The interpolated value of is calculated.

The data of this interpolation value is transferred to the memory 10b and overwritten on the portion which is no longer necessary for the interpolation calculation.

The reason why the interpolation value data can be overwritten in the memory 10b is as follows.

For example, Table 1 shows the relationship between the input line, the line data of the input field signal, and the output line data.

[0034]

[Table 1]

That is, as shown in the relationship of input / output data in Table 1, the order of data to be passed to the next stage is as follows.
For example, the image data of the (n-1) th line (output from the memory 10a), the image data of the interpolation line calculated next from the data of the (n-1) th line and the nth line, and then the same data as the nth line. The image data of the (n + 1) th line (or the nth line itself) will be delivered to the next stage.

When the image data is delivered to the next stage in such an order, the first necessary data is the (n-1) th line, the interpolation line, and the (n) th or (n + 1) th line.
That is, there is data that must be output for two lines before outputting the data for the nth line.

Further, considering that the n + 1-th line to be input next is the same as the n-th line, the data of the interpolation line is overwritten in the memory 10b holding the n-th line as described above. It becomes possible to do. That is, even if the data of the nth line is erased by the overwriting, if the data of the (n + 1) th line, which is the same data as the data of the nth line, is input, the same data can be obtained. .

When the memory 10b is overwritten with the data of the (n + 1) th line, the interpolation data register 1
Data of one pixel in the past, which is the result of the interpolation by the interpolation calculation circuit 14, is written and stored in 5 and used as data for the next interpolation calculation.

As a result, normally, the line buffers required for the interpolation calculation are two line buffers for holding the data of two lines of the input field and one line buffer for holding the line data of the interpolation result. In contrast to this, the interpolation circuit of the present embodiment can perform the interpolation calculation with only two line buffers. That is, in the circuit of the present embodiment, by overwriting the line data of the interpolation result in either one of the line buffers holding the data of two lines of the input field,
One line buffer for the interpolation line can be reduced. This is the data used for interpolation calculation
The same thing can be said even if it is above the line.

Next, the interpolation method used in the interpolation circuit of this embodiment will be described below.

Here, the line buffer memory 10a
And 10b to output the registers a _m , a _{m + 1} , a _{m + 2} , a _{m + 3} , a _{m + 4} , a _{m + 5} , a of the shift register 13 a.
_{m + 6} and each register b _m , b of the shift register 13b
_The data (data of the existing line) stored in _{m + 1} , b _{m + 2} , b _{m + 3} , b _{m + 4} , b _{m + 5} , b _{m + 6} is shifted, for example, as shown in FIG. In the register 13a, A _i , B
_i , C _i , D _i , E _i , F _i , and G _i are data, and in the shift register 13b, A _{i + 1} , B _{i + 1} ,
It is assumed that the data are C _{i + 1} , D _{i + 1} , E _{i + 1} , F _{i + 1} , and G _{i + 1} . In addition, these shift registers 13
Letting X be the data of the interpolated pixel calculated using the data stored in a and 13b, X _k in the drawing of FIG. 2 represents the pixel currently interpolated, and X _k-2 is two pixels before X _k. the interpolation pixel, X _k-1 is the interpolation pixel one pixel before the X _k, X _{k + 1} represents the pixel to be interpolated in the following X _k.

Here, in the interpolation calculation circuit 14 of the interpolation circuit of this embodiment, when the pixel x _k is obtained by the interpolation calculation, each of the 7 pixels as shown in FIG. 2 stored in the two shift registers 13a and 13b. Of the (7 × 2 pixels) data, first, pattern recognition is performed using the data of each three pixels (that is, 3 × 2 pixels) of two existing lines surrounded by broken lines in FIG.

At the time of this pattern recognition, first, the magnitude relationship between adjacent pixels in the vertical and horizontal directions is obtained. That is, when the pixel X _k is obtained by interpolation calculation, C _i , D _i , E _{i of the} pixel data stored in the shift register 13a and C _{i + 1} , of the pixel data stored in the shift register 13b, Using D _{i + 1} and E _{i + 1} , the size relation of the pixels adjacent in the vertical and horizontal directions is obtained. However, the magnitude relation between D _i and D _{i + 1} is excluded.

At this time, there are 6 combinations of adjacent pixels. Considering 3 combinations of equal sign and inequality sign for each of them, the size of the 3 × 2 pixel area surrounded by the broken line in FIG. 2 is considered. Combination by relationship (ie pattern)
There are 3 ⁶ types (= 729 types). The interpolation calculation circuit 14 recognizes the 729 patterns and determines whether or not to further expand the recognition area.

At this point, if it is known that the recognized pattern is a pattern in which the amount of information does not change much even if the recognition area is further expanded, or a pattern that cannot be recognized in the recognition area of maximum 7 × 2 pixels. , The interpolation value x _k is _obtained from the 3 × 2 pixel recognition area.

On the other hand, if the pattern is judged to be capable of more accurate pattern recognition by further expanding the recognition area of 3 × 2 pixels, the recognition area further expanded than the recognition area of 3 × 2 pixels. (In this case, the maximum is 7 ×
Pattern recognition is performed by (it can be expanded to a recognition area of 2 pixels).

The algorithm of the above interpolation calculation will be schematically described with reference to FIG. In FIG. 3, step S1
First, pattern recognition is performed in the 3 × 2 pixel area. In the next step S2, it is judged whether or not the recognition area should be further expanded. If it is judged that the recognition area should be further expanded (Yes), the processing advances to step S3, and if it is judged not to be expanded (no), the processing advances to step S4.

In step S4, Tables 2 to 10 described later are used.
Pattern recognition is performed in the 3 × 2 pixel area by referring to the table shown in FIG. 3, and in the next step S6, the optimum one is selected from the following three formulas to determine the interpolation calculation. X _k = (C _i + E _{i + 1} ) / 2 X _k = (D _i + D _{i + 1} ) / 2 X _k = (E _i + C _{i + 1} ) / 2

Further, in step S3, Tables 2 to 2 described later are
Pattern recognition is performed in the 7 × 2 pixel area with reference to the table shown in Table 10, and in the next step S5, the optimum one is selected from the following eight expressions to determine the interpolation calculation. X _k = (A _i + G _{i + 1} ) / 2 X _k = (B _i + F _{i + 1} ) / 2 X _k = (C _i + E _{i + 1} ) / 2 X _k = (D _i + D _{i + 1} ). / 2 X _k = (D _i + D _{i + 1} + 2X _k-1 ) / 4 X _k = (E _i + C _{i + 1} ) / 2 X _k = (F _i + B _{i + 1} ) / 2 X _k = (G _i + A _{i + 1} ) / 2

That is, in this embodiment, as described above,
When the pattern recognition area is a pattern in which the amount of information does not change much even if the area is widened, an interpolation value is obtained from the 3 × 2 pixel recognition area by referring to tables shown in Tables 2 to 10 described later. If the pattern is judged to be more accurate pattern recognition by expanding the pattern recognition area, Table 2 to be described later
By obtaining the interpolation value from the area of 7 × 2 pixels by referring to the table shown in Table 10, the scale of the pattern recognition circuit is suppressed from increasing while keeping the image quality after interpolation high.

For example, assuming that the entire area of 7 × 2 pixels is a pattern recognition area from the beginning, the combination (that is, pattern) of the magnitude relation between the adjacent pixels is 3 ¹⁸
(= 387420489), and it is very difficult to determine the interpolation calculation method for each pattern by performing pattern recognition, and it seems that the circuit scale becomes too large. In the embodiment, as described above, first, the recognition is performed in the area of 3 × 2 pixels,
After that, by adaptively expanding the area to a maximum of 7 × 2 pixels, the number of combinations to be considered is reduced. Even when the area is further expanded to 7 × 2 pixels, the equations for the interpolation calculation are only the above eight equations. It is suppressed from growing. In the circuit of this embodiment, the number of combinations (patterns) is reduced to about 920.

The above-described interpolation calculation will be described below with reference to more specific examples. In the example of FIG. 2, when obtaining the interpolated pixel X _i , the pixel C _i inside the broken line in FIG.
It is determined whether the interpolation direction is diagonal or vertical based on the magnitude relation between the six data D _i , E _i and the six data C _{i + 1} , D _{i + 1} , E _{i + 1} . Tables 2 to 10 show tables showing the interpolation directions determined by the magnitude relationship. These tables show the number of combinations of the above 6 pixels, 3 ⁶ =
It corresponds to 729.

[0053]

[Table 2]

[0054]

[Table 3]

[0055]

[Table 4]

[0056]

[Table 5]

[0057]

[Table 6]

[0058]

[Table 7]

[0059]

[Table 8]

[0060]

[Table 9]

[0061]

[Table 10]

According to these tables, the interpolated pixel X is determined as follows according to the blank mark, the / mark, and the \ mark in each table by the pattern recognition of the 3 × 2 pixel area. No mark X = (D _i + D _{i + 1} ) / 2 / mark X = (E _i + C _{i + 1} ) / 2 \ mark X = (C _i + E _{i + 1} ) / 2

However, D is placed beside or above the / and \ marks in the table.
_{When i} > C _{i + 1} , D _{i + 1} > C _i , D _i ≦ E _{i + 1} , ..., It means that the diagonal interpolation is performed only when the condition is satisfied. . Also on the table ~
The portion of indicates a portion where an interpolated image is obtained by pattern recognition of a 7 × 2 pixel area described later.

The rows and columns of the tables in Tables 2 to 10 are numbered from 0 to 26, respectively, where the row number is q and the column number is r, and each matrix in the table is coordinated. When expressed as (r, q), interpolation is performed from the data of 7 × 2 pixels for the coordinate portion on the table indicated by the following.

(0,12), (9,12) (14,2), (14,11) (14,23), (14,26) (21,12), (24,12)

(17,14), (26,14) (12,15), (12,24) (12,0), (12,3) (2,14), (5,14)

(26,0), (0,26)

(7, 13), (8, 14), (12, 6), (13,
7) (12,19), (13,20), (18,12),
(19,13)

(0,23), (9,26), (17,0), (26,
3) (0,17), (3,26), (23,0), (26,
9)

The interpolation algorithm in the area where the pattern recognition is performed by 7 × 2 pixels shown in the coordinate parts of these tables will be described below.

First, the interpolation of the coordinate portion in the table
As an example, for example, C_i<D_i<E _i> E_{i + 1}= D_{i + 1}
= C_{i + 1}<C_iIn case of, the large and small size of the flowchart of FIG. 4
Do another and interpolate. In other words, search for smaller data.
Interpolation is performed. The above C_i<D_i<E_i
> E_{i + 1}= D_{i + 1}= C_{i + 1}<C_iIs (r, q) in Table 7.
This is an example corresponding to the coordinates = (24,12).

That is, in FIG. 4, step S
B in 10_i<C_iAnd E_{i + 1}= F _{i + 1}Whether or not
The judgment is made, and if the judgment is NO, step S11.
If the answer is yes, then go to step S12.

In step S11, X _k = (C _i + E
_{i + 1} ) / 2 is calculated to obtain the interpolated value. Step S
In step 12, if it is determined that A _i <B _i , the process proceeds to step S13 if the result is NO, and to step S14 if the result is YES.

In step S13, X _k = (B _i + F
_{i + 1} ) / 2 is calculated to obtain the interpolated value, and step S1
In step 4, X _k = (A _i + G _{i + 1} ) / 2 is calculated to obtain an interpolated value.

Next, in the interpolation of the part, for example, C _i >
When D _i > E _i <E _{i + 1} = D _{i + 1} = C _{i + 1} > C _i , FIG.
Interpolation is performed by determining the size of the flow chart. That is, interpolation is performed by performing the process of searching for the larger data. Note that this C _i > D _i > E _i <E _{i + 1} = D _{i + 1} = C _{i + 1} >
C _i is an example corresponding to the coordinates (r, q) = (2, 14) in Table 5.

That is, in FIG. 5, step S
B at 20_i> C_iAnd E_{i + 1}= F _{i + 1}Whether or not
If the judgment is made and the judgment is NO, step S21.
If the answer is yes, then go to step S22.

In step S21, X _k = (C _i + E
_{i + 1} ) / 2 is calculated to obtain the interpolated value. Step S
At 22, it is judged whether A _i > B _i . If it is judged as no, the process proceeds to step S23, and if it is judged as yes, the process proceeds to step S24.

In step S23, X _k = (B _i + F
_{i + 1} ) / 2 is calculated to obtain the interpolated value, and step S2
In step 4, X _k = (A _i + G _{i + 1} ) / 2 is calculated to obtain an interpolated value.

Here, in the interpolation calculation of the portions of and, both upper and lower limits of the interpolation value X _k are set. That is, D _i <X _k <D _{i + 1} or D _i > X _k > D
_{When the} upper and lower limits are set like _{i + 1} and the interpolation result X _k satisfies this relationship, the interpolation value X _k is adopted as it is.
When this relationship is not satisfied, the innermost diagonal interpolation value is set to X _k . That is, X _k = (E
Let _i + C _{i + 1} ) / 2 be the interpolation result, and X _k = (C _i + E _{i + 1} ) / 2 be the interpolation result at the time of the interpolation calculation of the portion.

Next, in the interpolation calculation of the portion, for example, C
_i<D_i<E_i> E_{i + 1}<D_{i + 1}<C_{i + 1}> C_itime,
C_iAnd E_{i + 1}Is there a valley of magnitude relation with
_iAnd C_{i + 1}I don't know if there is a ridge of magnitude relation with.
Therefore, interpolation is performed under the following conditions. The interpolation calculation
C above in_i<D_i<E_i> E_{i + 1}<D_{i + 1}<C
_{i + 1}> C_iIn the case of a pattern in which all signs of
Is C_iAnd E_{i + 1}Ridge between, E_iAnd C_{i + 1}Between the valley
Like Also, C_i<D_i<E_i> E_{i + 1}<D_{i + 1}
<C_{i + 1}> C_iOf (r, q) = (26,0) in Table 4
It is an example corresponding to coordinates.

At this time, the judgment of the ridge or the valley of the above-mentioned magnitude relation is made according to the following criteria. For example, if the magnitude relationship of A _{i to} E _i is as follows, it is assumed that there is a valley in B _i or C _i .

A _i > B _i <C _i <D _i <E _i , or A
_i > B _i = C _i <D _i <E _i , or A _i > B _i > C _i
<D _i <E _i

Therefore, if there is no magnitude relation between B _i and C _i, and if the magnitude relation between A _i and B _i is A _i > B _i , it is judged that there is a valley.

Here, as the first condition, A _i > B _i ,
And F _{i + 1} <G _{i + 1} , it is determined whether or not there is a valley in B _i or C _i and whether or not there is a valley in E _{i + 1} or F _{i + 1.} When there is _one, Q ₁ = 1 and when there is no valley in either one or both, Q ₁ = 0.

As the second condition, A _{i + 1} <
When B _{i + 1} and F _i > G _i , it is determined whether or not there is a ridge at B _{i + 1} or C _{i + 1} and whether or not there is a ridge at E _i or F _i. If there is a ridge, Q ₂ = 1; if there is no ridge on either or both, then Q ₂ = 0.

At this point, the interpolation method is first determined as follows. If Q ₁ = 1 and Q ₂ = 1 then X _k = (D _i + D _{i + 1} ) /
If 2 Q ₁ = 1 and Q ₂ = 0, then X _k = (C _i + E _{i + 1} ) /
If 2 Q ₁ = 0 and Q ₂ = 1 then X _k = (E _i + C _{i + 1} ) /
2 If Q ₁ = 0 and Q ₂ = 0, the next judgment is made.

Next, as the third condition, when A _i > B _i or F _{i + 1} <G _{i + 1} , there is a valley in B _i or C _i or E _{i + 1} or F _{i + 1.} If there is a valley on either side, set Q ₃ = 1. If there is no valley on either side, Q
₃ = 0.

As the fourth upper limit, A _{i + 1} <
When B _{i + 1} or F _i > G _i , it is determined whether or not there is a ridge in B _{i + 1} or C _{i + 1} or E _i or F _{i. 4} = 1 and when none have ridges, set Q ₄ = 0.

As the fifth condition, C _i = E _{i + 1} , or C
_In the judgment of _i = F _{i + 1} , or B _i = E _{i + 1} , or B _i = F _{i + 1} , when yes, Q ₅ = 1 and when no, Q _{5
Set 5} = 0.

As a sixth condition, E _i = C _{i + 1} , or E
_In the judgment of _i = B _{i + 1} , or F _i = C _{i + 1} , or F _i = B _{i + 1} , when yes, Q ₆ = 1 and when no, Q
₆ = 0.

From the above conditions, the interpolation method is finally determined as follows. That is, Q ₃ = 1 and Q ₄ = 1 and Q
_{If 5} = X _K and Q ₆ = X _K, then X _K = (D _i + D _{i + 1} ) /
2. If Q ₃ = 1, Q ₄ = 0, Q ₅ = X _K , Q ₆ = 1 then X _K = (E _i + C _{i + 1} ) / 2, and Q ₃ = 0, Q ₄
= 1 and Q ₅ = 1 and Q ₆ = X _K , X _K = (C _i + E
_{i + 1} ) / 2, Q ₃ = 0, Q ₄ = 0, Q ₅ = X _K , Q
_{If 6} = X _K, then X _K = (D _i + D _{i + 1} ) / 2. However, Q ₁ = Q ₂ = 0.

Next, in the interpolation calculation of the portion, the pixel to the left of the interpolated pixel X _k is X _k-1 , for example, C _i <D _i > E
_{When i} > E _{i + 1} = D _{i + 1} = C _{i + 1} <C _i , interpolation is performed under the following conditions. Note that C _i <D _i > E _i > E _{i + 1} = D _{i + 1}
= C _{i + 1} <C _i is (r, q) = (18,12) in Table 7.
It is an example corresponding to the coordinates of.

For example, as the condition, C _{i + 1} = X _k-1
If yes, Q ₇ = 1 and if no, Q ₇ = 0. The interpolation method at this time is X _k = (D _i + D _{i + 1} ) / 2 if Q ₇ = 0 and X if Q ₇ = 1.
_{Let k} = (D _i + C _{i + 1} + 2X _k−1 ) / 4.

Next, in the interpolation of the part, D _i and D _{i + 1}
The interpolation pixel between an X _k, for example, C _i = D _i <E _i
When> E _{i + 1} <D _{i + 1} <C _{i + 1} > C _i , interpolation is performed under the following conditions. Note that C _i = D _i <E _i > E _{i + 1} <D _{i + 1} <C
_{i + 1} > C _i is an example corresponding to the coordinates (r, q) = (17,0) in Table 3.

For example, as the condition, C _i = E _{i + 1} ,
Or C _i = F _{i + 1} , or B _i = E _{i + 1} , or B _i = F
_In the judgment of _{i + 1} , if yes, Q ₈ = 1 and if no, Q ₈ = 0. The interpolation method at this time is Q ₈ =
If 1, then X _k = (C _i + E _{i + 1} ) / 2, and if Q ₈ = 0, then X _k = (D _i + D _{i + 1} ) / 2.

Further, as a condition at the time of each of the above-mentioned size discrimination, the size discrimination of two data is performed under the following conditions. That is, if one data is Y and the other data is W, then Y = W if INT ((Y-W) / L) = 0 and INT ((Y-W) / L)> 0. If there is Y> W, if INT ((Y−W) / L) <0, then Y <W. Note that INT is a built-in function.

Here, the range of ± (L-1) depending on L is regarded as an equal sign. For L, use 1 or 4 or 8 or 16. The value of L is changed according to the SN ratio required by the image, and the smaller the value becomes, the more sensitive the value becomes.
The reference to the area of × 2 pixels is reduced.

The following effects can be obtained by using the algorithm of the interpolation calculation of the above-mentioned parts (1) to (3).

First, by using the interpolation calculation algorithm of the portions and, when two regions have diagonal boundaries, interpolation can be performed so that the boundaries become smooth.

For example, as a first specific example of the image before and after the interpolation in FIG. 6, the effect of the above-described interpolation calculation will be described. Further, each cell in FIG. 6 corresponds to each pixel data in FIG. 2, and the pixel data in each cell in FIG. 6 is also an example of pixel data stored in each register of the shift register 13 in FIG. . Even in the interpolation calculation of the above part, the same effect can be obtained by performing the interpolation calculation according to the tables of Tables 2 to 10.

As a first specific example of this, as shown in FIG.
There is an image of the existing line (image before interpolation) as shown
Suppose At this time, each image of the existing line in FIG.
The color density of the element is expressed in hexadecimal notation.
In each pixel A_i, B_i, C _i, D_i, E_i, F_i, G
_iThe actual data of color density is (10) (50) (70)
(90) (F0) (F0) (F0), which is the existing lower side
Each pixel A in the line_{i + 1}, B_{i + 1}, C_{i + 1}, D_{i + 1}, E
_{i + 1}, F_{i + 1}, G_{i + 1}The actual data of the color density of (1
0) (10) (10) (10) (10) (10) (1
0). In addition, (10) represents a dark color,
The color becomes lighter as it goes to (F0).

That is, the positional relationship between the interpolated pixel X _k shown in FIG. 2 and the pixels of each existing line is as follows: existing line (10) (50) (70) (90) (F0) (F0) ( F0) Interpolation line X _k Existing line (10) (10) (10) (10) (10) (10) (10) If the interpolation line X _k is 3 × 2 pixels above and below the existing line C _i , D _i , E _i and C _{i + 1} ,
Regarding the magnitude relationship between D _{i + 1} and E _{i + 1} , the three pixels in the upper existing line are (70) (90) (F0) in order from the left, and the three pixels in the lower existing line are (10) (10). ) Since it is (10), (70) <(90) <(F0)>
(10) = (10) = (10) <(70).

In this case, the pattern recognition area is enlarged,
Recognize the size relationship of the remaining pixels. That is, this FIG.
In case of (a), A_i, B_i, C_iAnd E_i, F_i, G
_i, And A_{i + 1}, B_{i + 1}, C_{i + 1}And E_{i + 1}, F_{i + 1}, G
_{i + 1}The size relationship of_i<B _i<C_iAnd E_i= F_i= G
_i, And A_{i + 1}= B_{i + 1}= C_{i + 1}And E_{i + 1}= F_{i + 1}= G
_{i + 1}Then, from the matrix of 7 × 2 pixels, X_k= (A
_i+ G_{i + 1}) / 2 interpolation formula is determined.

That is, the example shown in FIG.
As an example of the interpolation calculation of the above part, (r,
q) = (24,12) is an example corresponding to the coordinates, and C_i
<D _i<E_i> E_{i + 1}= D_{i + 1}= C_{i + 1}<C_iBecome
There is. Therefore, the size of the flowchart of FIG.
It discriminates and interpolates.

Specifically, toward the smaller data
Find the pattern, B_i<C_iAnd E _{i + 1}= F_{i + 1}Is
It is determined whether or not (step S10 in FIG. 4)
In the example of (a) of 6, B_iIs (50) and C_iBut (7
E in 0)_{i + 1}And F_{i + 1}Were both (10)
Therefore, (50) <(70) and (10) = (10)
Because it is judged as yes, further A_i<B_iThe judgment of
Perform (step S12 of FIG. 4). In this judgment, the figure
In the example of 6 (a), A_iBut in (10) B_iIs (50)
Therefore, in step S12 of FIG.
Determined, and therefore X in step S14 of FIG._k=
(A_i+ G_{i + 1}) / 2 interpolation calculation is performed. This allows
X_k= (10 + 10) / 2 and the interpolation value (this
If it is (10)).

The above interpolated pixel X in FIG._kInterpolation pixel other than X
_k-3, X_k-2, X_k-1, X_{k + 1}, X _{k + 2}, X_k-3Against
The interpolation calculation according to the tables in Tables 2 to 10 above.
By performing the above, from the image before interpolation in FIG.
You can get the interpolated image as shown in (b).
Swell.

That is, if the interpolation calculation of this embodiment is performed, the image of the diagonal line of the image before the interpolation can be smoothly interpolated. Further, according to the interpolation calculation of the present embodiment, it seems appropriate that the interpolated value is between the pixel values of the upper and lower existing lines, so that the value of the interpolated value is limited to the range of the upper and lower pixel values. Therefore, the noise can be reduced. For example, in the case of a color image, noise such as cyan and magenta is reduced at the edge of the image.

Next, by using the interpolation calculation algorithm of the portions and, it is possible to more smoothly interpolate the image of the diagonal line of the image before the interpolation.

For example, as a second specific example of the image before and after the interpolation in FIG. 7, the effect of the interpolation calculation of the above portion will be described. Further, FIG. 7 also shows the same as FIG. 6 described above. Even in the interpolation calculation of the above part, the same effect can be obtained by performing the interpolation calculation according to the tables of Tables 2 to 10.

As a second specific example, as shown in FIG.
There is an image of the existing line (image before interpolation) as shown
Suppose At this time, each image of the existing line in FIG.
The color density of the element is expressed in hexadecimal notation.
In each pixel A_i, B_i, C _i, D_i, E_i, F_i, G
_iActual data of color density is (10) (10) (10)
(70) (F0) (70) (10), existing below
Each pixel A in the line_{i + 1}, B_{i + 1}, C_{i + 1}, D_{i + 1}, E
_{i + 1}, F_{i + 1}, G_{i + 1}The actual data of the color density of (1
0) (70) (F0) (70) (10) (10) (1
0).

That is, the positional relationship between the interpolated pixel X _k represented in correspondence with FIG. 2 and the pixels of each existing line is as follows: existing line (10) (10) (10) (70) (F0) (70) ( 10) Interpolation line X _k existing line (10) (70) (F0) (70) (10) (10) (10) If the interpolation pixel X _k is 3 × 2 pixels above and below the existing line C _i , D _i , E _i and C _{i + 1} ,
The magnitude relationship between D _{i + 1} and E _{i + 1} is (10) (70) (F0) from the left in the upper three existing lines, and (F0) (70) from the lower three existing lines. ) (10), so (10) <(70) <(F0)>
(10) <(70) <(F0)> (10).

In this case, the example of (a) of FIG. 7 corresponds to (r,
q) = (26,0), where C _i <
D _i <E _i > E _{i + 1} <D _{i + 1} <C _{i + 1} > C _i . Therefore, the interpolation calculation is performed according to each condition as described in the above-mentioned interpolation of the portion.

Specifically, it is determined whether a ridge or a valley is based on the size relation of the pixels of each existing line. This (a) of FIG.
In the above example, the pixel values of the upper existing line are (10) (1
0) (10) (70) (F0) (70) (10) and therefore A _i = B _i = C _i <D _i <E _i > F _i.
> G _i , and E _i is a ridge. The pixel values of the lower existing line are (10) (70) (F0) (70).
(10) (10) (10), so A _{i + 1}
<B _{i + 1} <C _{i + 1} > D _{i + 1} > E _{i + 1} = F _{i + 1} = G _{i + 1} , and C _{i + 1} is a ridge.

That is, since there is no valley in the upper existing line B _i or C _i and the lower existing line E _{i + 1} or F _{i + 1} under the above-mentioned first condition, Q ₁ = 0, Further, under the conditions of FIG. 2 described above, Q ₂ = 1 indicating that both the upper and lower existing lines B _{i + 1} or C _{i + 1} and E _i or F _i have a ridge, and therefore, As described above, as the interpolation method at the time point, since Q ₁ = 0 and Q ₂ = 1 are used, the interpolation calculation of X _k = (E _i + C _{i + 1} ) / 2 is performed.

As a result, X _k = (F0 + F0) / 2 is calculated to obtain the interpolated value ((F0) in this case).

In the example of FIG. 7, since the interpolation calculation expression can be obtained up to the second condition, the third condition can be obtained.
The conditions # 6 to # 6 are not determined.

[0117] with respect to FIG. 7 of the interpolation pixel X _k other than the interpolation pixel _{X k-3, X k-} 2, X k-1, X k + 1, X k + 2, X k-3 is By performing the interpolation calculation according to the tables in Tables 2 to 10, the image before the interpolation in FIG.
It is possible to obtain an image after interpolation as shown in (b) of FIG.

Next, the effect of the algorithm of the interpolation calculation of the above portion will be described with reference to FIG. 8 as a third concrete example. 8B and 8C are also shown in the same manner as FIGS. 6A and 6B described above. In addition, this FIG.
(A) shows an entire image 100, an example image 102 therein, and an image area 101 stored in the shift register 13. That is, in FIG. 9, an example in which interpolation is performed on the apex portion of the triangular image 100 will be described.

The third specific example is shown in FIG.
There is an existing line image (image before interpolation) that
Will be. At this time, each of the existing lines in FIG.
The pixel color density is expressed in hexadecimal notation and the existing line above
Each pixel A_i, B_i, C_i, D_i, E_i, F_i, G_iof
Actual data of color density is (F0) (F0) (F0) (F
0) (F0) (F0) (F0), and the existing lower line
Each pixel A_{i + 1}, B _{i + 1}, C_{i + 1}, D_{i + 1}, E_{i + 1},
F_{i + 1}, G_{i + 1}The actual data of color density of (F0) (F
0) (70) (10) (70) (F0) (F0)
And

That is, the positional relationship between the interpolated pixel X _k shown in FIG. 2 and the pixels of each existing line is the existing line (F0) (F0) (F0) (F0) (F0) (F0) ( F0) Interpolation line X _k Existing line (F0) (F0) (70) (10) (70) (F0) (F0) If the interpolation pixel X _k is 3 × 2 pixels above and below the existing line C _i , D _i , E _i and C _{i + 1} ,
Regarding the magnitude relationship between D _{i + 1} and E _{i + 1} , the three pixels in the upper existing line are (F0) (F0) (F0) in order from the left, and the three pixels in the lower existing line are (70) (10). ) (70), so (F0) = (F0) = (F0)>
(70)> (10) <(70) <(F0).

That is, in the example of FIG. 8B, C _i = D _i = E as an example of the interpolation calculation of the above-mentioned portion.
_This shows the case where _i > E _{i + 1} > D _{i + 1} <C _{i + 1} <C _{i. In} the example corresponding to the coordinates (r, q) = (12, 6) in Table 3 above. Therefore, the interpolation calculation is performed according to each condition as described in the interpolation of the above-mentioned portion.

[0122] In this case, pattern recognition region to expand, and the interpolating pixel X _k-1 and C _i for one place to the left of the previous is a need in the interpolation operation of the interpolation pixel X _k, C _i = X _{k -1} judgment is made. In the example of FIG. 8B, since C _i = X _k−1 , Q ₇ = 0, and the interpolation calculation at this time is
As described above, X _k = (D _i + D _{i + 1} + 2X _k-1 ) / 4
Becomes

[0123] with respect to the interpolation pixel _{X k-3, X k-} 2, X k-1, X k + 1, X k + 2, X k-3 other than the interpolation pixel X _k of FIG. 8, By performing the interpolation calculation according to the tables in Tables 2 to 10, the image before the interpolation in FIG.
It becomes possible to obtain an image after interpolation as shown in (c) of FIG. That is, when only simple interpolation is performed as in the conventional interpolation method, the apex of FIG. 8A is extended and further emphasized so that it looks like a so-called mustache. According to the interpolation calculation of this embodiment,
The density at the extension of the apex is blurred and lightened, and the whisker-like image becomes inconspicuous.

Next, a concrete example of performing the interpolation calculation of 3 × 2 pixels according to the tables of Tables 2 to 10 will be described.

That is, as a fourth specific example, FIG.
Image of existing line as shown in (a) (image before interpolation)
Is present. Note that this FIG. 9 is similar to FIG. 6 described above.
It represents. At this time, each of the existing lines in FIG.
The color density of the pixel is expressed in hexadecimal notation.
Each pixel A in the line_i, B_i, C_i, D_i, E_i, F_i,
G _iThe actual data of the color density of (F0) (90) (6
0) (10) (60) (90) (F0),
Each pixel A on the existing line_{i + 1}, B_{i + 1}, C_{i + 1}, D_{i + 1},
E_{i + 1}, F_{i + 1}, G_{i + 1}The actual data of color density of (F
0) (90) (60) (10) (60) (90) (F
0).

That is, the interpolated image represented in correspondence with FIG.
Element X_kAnd the pixel relationship between each existing line and the existing line (F0) (90) (60) (10) (60) (90) (F0) Interpolation line X_k If the existing line is (F0) (90) (60) (10) (60) (90) (F0), this interpolation pixel X_kUp and down against
3 x 2 pixels C of existing line_i, D_i, E_iAnd C_{i + 1},
D_{i + 1}, E_{i + 1}The size relationship is the 3 lines of the existing line above
Element is (60) (10) (60) from left to right
3 pixels of the existing line of (60) (10) (60)
From that, C_i> D_i<E_i= E _{i + 1}> D_{i + 1}
<C_{i + 1}= C_iIt has become.

In this case, the pattern recognition area is not expanded, and the interpolation formula is determined from the matrix table of 3 × 2 pixels in Tables 2 to 10. Therefore, from the tables of Tables 2 to 10, the above C _i > D _i <E _i = E _{i + 1} > D _{i + 1} <C
The interpolation calculation formula in the case of _{i + 1} = C _i is X _k = (D _i + D
_{i + 1} ) / 2 is determined, whereby _Xk = (10 + 1
0) / 2 = 10 is calculated.

The interpolation pixel X in FIG._kInterpolation pixel other than X
_k-3, X_k-2, X_k-1, X_{k + 1}, X _{k + 2}, X_k-3Against
However, the interpolation calculation is performed according to the tables in Tables 2 to 10 above.
By performing this, the image before interpolation in FIG.
You can get the interpolated image as shown in (b).
Swell.

The interpolation by the above-described interpolation algorithm in the interpolation circuit of this embodiment is performed in the sub-scanning direction of the video printer, and in the main scanning direction, the interpolation is performed by the simple average of the pixels before and after. . The order of interpolation is the sub-scanning direction and the main scanning direction. Further, when quadruple interpolation is necessary, the interpolation is performed twice.

Here, the simple average in the main scanning direction is used for the following reason. That is, if the same algorithm as in the sub-scanning direction is used, a 7-line memory is required, which significantly increases the cost. Also, increasing the number of dots by performing interpolation is equivalent to increasing the number of samplings. This is because the rising can be regarded as linear to some extent, and in this case, it should not be erroneous even if the average of the pixels before and after is used as the interpolation value.
If the rising edge of the signal is a sampling signal of 5 fsc at about 200 ns, then about 4 dots are used for the rising edge.

Further, a simple average is adopted in the main scanning direction for the above-mentioned reason, and the sub-scanning direction interpolation is performed before interpolation in the main scanning direction so that a substantial pattern recognition area can be taken. Therefore, the order of the interpolation direction is the order of the sub scanning direction and the main scanning direction as described above.

The size of the recognition area when the pattern recognition area is enlarged can be made larger than the 7 × 2 pixel area. For example, when expanding the area in the direction of increasing the number of lines, for example, 7 × 4 pixels,
7 × 6 pixels can be taken as an example, and in this case, better interpolation can be performed. For example, it is an L-shaped area.

As described above, in the interpolation circuit of the embodiment of the present invention, since the adaptive interpolation is performed, the image quality is further improved, and particularly the image quality is improved in terms of diagonal resolution and jerkiness. You can Moreover, the circuit scale is not so large, which is practical. Furthermore, the image quality in still image output can be expected to be significantly improved.

[0134]

As is apparent from the above description, in the television signal interpolation circuit of the present invention, the same line data of the original signal of one field is supplied v times and stored in w line buffers. , An interpolation calculation is performed using data of a predetermined area stored in each of these line buffers, and the interpolation data is overwritten on a portion of the w line buffers in which the data after the interpolation calculation is stored, It is not necessary to newly provide a memory for interpolation data, and it is possible to reduce the circuit scale. Further, with the interpolation circuit of the present invention, it is possible to obtain a sufficient interpolated image in terms of gradation, resolution, and jerkiness, even for an oblique image.

[Brief description of drawings]

FIG. 1 is a block circuit diagram showing a schematic configuration of a television signal interpolation circuit according to an embodiment of the present invention.

FIG. 2 is a diagram for explaining data of a work table.

FIG. 3 is a flowchart of an interpolation algorithm.

FIG. 4 is a flowchart showing an example of an interpolation algorithm when performing interpolation calculation by pattern recognition of 7 × 2 pixels.

FIG. 5 is a flowchart showing another example of an interpolation algorithm when performing interpolation calculation by pattern recognition of 7 × 2 pixels.

FIG. 6 is a diagram showing an image of a first specific example for explaining an interpolation calculation by pattern recognition of 7 × 2 pixels.

FIG. 7 is a diagram showing an image of a second specific example for explaining an interpolation calculation by pattern recognition of 7 × 2 pixels.

FIG. 8 is a diagram showing an image of a third specific example for explaining an interpolation calculation by pattern recognition of 7 × 2 pixels.

FIG. 9 is a diagram showing an image of a fourth specific example for explaining an interpolation calculation by pattern recognition of 3 × 2 pixels.

[Explanation of Codes] 1 Input control circuit 7 Transfer control circuit 9 Work table transfer control circuit 10a, 10b Line buffer memory 13 Shift register 14 Interpolation calculation circuit 15 Interpolation register

Claims (1)

[Claims] 1. An interpolating circuit for a television signal for generating a signal of one frame from an original signal of one field of a television signal, w pieces of which store line data of the original signal of one field (w is 2 or more). Line buffer, line data supply means for outputting the same line data v times to supply the w line buffers, and interpolation data using predetermined area data stored in the w line buffers. Interpolating means for performing interpolation of the television signal, characterized in that the interpolation data by the above-mentioned interpolation calculating means is overwritten on the portion of the w line buffers where the data for which the interpolation operation has been completed is stored. circuit.