JPH0440074A - Picture encoding device - Google Patents

Abstract

PURPOSE:To efficiently compress a picture data while suppressing the degradation of picture quality by executing the various types of encoding to a black line picture part and a part excepting for the black line picture part. CONSTITUTION:A means 15 is provided to decide a black character, a means 19 is provided to detect the colorless part of a picture element around the black character, a means 21 is provided to subtract the black character part and the colorless part from an original picture for the unit of a picture element and to replace the subtracted part with the average value of a surrounding color, and encoding means 18 and 23 are provided to execute the various types of encoding to the black line picture part and the part excepting for the black line picture part. While using a luminance (Y) signal, the edge of the colorless part only is emphasized without imbalancing the colors. Therefore, it is possible to sharply reproduce the detailed part of the black character which is read while being slightly crushed in the case of inputting the picture. Thus, the accuracy and efficiency of detecting and encoding a black character pattern can be improved.

Description

DETAILED DESCRIPTION OF THE INVENTION [Field of Industrial Application] The present invention relates to an image encoding device such as a color facsimile device that separates and encodes characters and natural image portions in a color image.

[Conventional technology]

Conventionally, as a method for encoding a color image, a method has been known in which the image is divided into blocks, subjected to orthogonal transformation, and then the coefficients thereof are quantized and encoded.

[Problem that the invention is trying to solve]

However, in the above conventional example, since the coefficients after orthogonal transformation are quantized, high frequency components are lost and ringing occurs at the edges. (including images with black lines, etc.) was degraded.

Also, in order to improve the quality of black text, it may be possible to encode the black text and other parts separately, but simply extracting the black text will not work for images read from a scanner, for example. The other portions include the surrounding portions of black characters, which further form edge portions, which reduce the efficiency of orthogonal transform encoding.

Furthermore, when printing a hard copy of the decoded image in four colors of YMCK, it is necessary to create a black signal for printing black character parts in a single black color, which makes the procedure complicated.

SUMMARY OF THE INVENTION Therefore, an object of the present invention is to provide an apparatus that can eliminate the drawbacks of the prior art as described above and perform efficient image encoding while maintaining high image quality.

Another object of the present invention is to provide an image encoding device suitable for reproducing black character portions in a color image.

[Means and effects for solving the problem] The image encoding device of the present invention has been made in view of the above points, and includes means for detecting a black line drawing portion of input image data and expanding the black line drawing portion. A first feature of the present invention is that the image forming apparatus includes an encoding means for performing different encoding on a black line drawing portion detected by the black line both portion detection means and a portion other than the black line both portions.

Further, means for detecting a line drawing portion of input image data, means for expanding the line drawing portion detected by the detecting means, and replacing the line drawing portion expanded by the expanding means in accordance with values of surrounding image data. A second feature is that the image forming apparatus includes means and means for encoding the image data replaced by the replacing means.

〔Example〕

In the embodiment of the present invention described below, a means for determining a black character, a means for detecting an achromatic part of several pixels surrounding the black character, and a means for subtracting a black character part and an achromatic part from an original image pixel by pixel are used. Parts have a means of replacing them with the average value of surrounding colors. Edges are determined in block units, and then black characters are determined. A block that satisfies both conditions at the same time is defined as a black character block, and is binarized using a fixed threshold. Apply this to the entire image to create a black text surface. Next, a black character is considered pixel by pixel, and the achromaticity of, for example, eight surrounding pixels of the pixels constituting the black character is checked, and if they are achromatic, they are considered to be part of the black character. Consider this as the surface surrounding the black text, separate from the surface of the black text. The surface of the black text and the surface surrounding the black text are subtracted pixel by pixel from the original image, and the subtracted portion is replaced with the average value of the surrounding colors.

As described above, create a black text side and a natural image side.

The surface of the black character image and the surface of the natural image thus created are respectively encoded using arithmetic coding and orthogonal transformation coding to obtain code data.

This will be explained below using the drawings.

FIG. 1 is a block diagram showing an embodiment of the present invention. 1
0 is an image input device, 11 is a YCrCb conversion unit, 12 is an edge emphasis unit, 13 is a frame memory, 14 is an edge detection unit, 15 is a black detection unit, 16 is a selector, 17 is a frame memory, and 18 is an arithmetic coding unit , 19 is an achromatic color determination section, 2
0 is a frame memory, 21 is a black character removal/average value replacement unit, 22 is a frame memory, 23 is an orthogonal transform encoding unit, 2
4 is an encoded data transmitter.

RGB data 101 from the image input device 10 is YCr
In the Cb conversion section, the conversion of equation (1) is performed, and Y,
Cr.

The Cb multiplied signal is stored in the edge emphasis section 12 and the Cr and Cb multiplied signal direct frame memory 13.

A signal "1" is output to the selector for the pixel, and "0" is output for the other pixels.

Y<Tyl (=50)
(2) The edge emphasis section 12 performs edge emphasis only on the Y signal, and outputs the result to the frame memory 13. The data in the frame memory 13 is read out in blocks of NXN (here N = 4, but it is better to match the block size of orthogonal transformation, which will be described later), and enters the edge detection section 14 and the black detection section 15. . The edge detection unit 14 uses only the input Y signal and detects a constant value (here, level 7 at 8-bit 256 levels), which is the difference between the maximum value and minimum value within the block.
If the value is larger than 0 (but is not limited to this value), it is assumed that an edge exists and outputs a switching signal "B" to the selector 16. Otherwise, it outputs "0". The switching signal continues to be output until black detection is performed for all pixels in the block.The data input to the black detection section 15 is transferred to the edge detection section 14 in the selector 16 that simultaneously satisfies the following equations (2) and (3). Depending on the switching signal from
If so, the signal from the black detection section 15 is output to the frame memory 17. Therefore, in a block where an edge exists, the signal from the black detection section 15 is always output to the frame memory 17, and if no edge exists, the signal 301 is output to the frame memory 17. When the above processing is completed, pixels detected as black characters are stored in the frame memory 17.

In the arithmetic encoding section 18, the black character pattern stored in the frame memory 17 is arithmetic encoded and output as code data to the encoded data transmitting section 24.

In this embodiment, arithmetic codes are used as means for encoding black character patterns, but MH, MR, MMR, etc. may also be used, and the present invention is not limited to this. In the achromatic color determination unit 19, for the black character stored in the frame memory 17, the surrounding 8
Achromatic color determination is performed on pixels, and pixels that satisfy equations (3) and (4) are determined to be achromatic pixels and stored in the frame memory 2.
Output to 0.

Y<Ty3 (=200)...(
4) If the signal value in the frame memory 20 is "1", that is, if it is part of a black character, the black character removal/average value replacement unit 21 calculates the value of the corresponding part of the original image data stored in the frame memory 13. Clear and replace with the average pixel value in the block. In the orthogonal transform encoding section 23 , discrete cosine transform (DCT) encoding is performed on the data output from the black character removal/average value replacement circuit 21 , and encoded data is output to the encoded data transmitting section 24 .

Next, the Y signal edge emphasizing section 12, which is the key point of the present invention, will be described.
Explain.

Normally, when fine parts of text are read by a scanner, the edges cannot be reproduced sharply; for example, two adjacent horizontal bars in small Mincho typeface become one. Even though edge enhancement is performed to reproduce edges sharply, normal RGB data read from a scanner cannot be used even if the document is completely black due to scanner precision and noise.
=G=B, and there will be variations. Therefore, this R
If the edges of the GB signals are emphasized for each signal, the dispersion will be further expanded, color shift will occur around black characters, the hue will change, and the accuracy of black character detection, which will be described later, will be reduced. As a result, edges remain in the image after the black characters have been removed, and these edges reduce the encoding efficiency of orthogonal transformation. Therefore, in this embodiment,
In order to perform edge emphasis without destroying the color balance of the black character part (achromatic part), edge emphasis is performed only when the pixel of interest satisfies equation (3) using only the luminance (Y) signal ((5
-A) formula). If not satisfied, nothing is done as in equation (5-B). In addition, in order to prevent noise from being emphasized, the absolute value of the filter output value F is set to Te as shown in FIG.
(=30) or less, edge enhancement is not performed ((5-
D) formula). Here, Y(i,j) indicates the pixel of interest, and k is a coefficient that controls the degree of edge emphasis.

Although it is set to = 1 here, it is not limited to this. For example, f
It may be made proportional to the value of (F). Further, FIG. 2(a) shows the arrangement of pixels expressed by equation (5-C).

YE (i, D = Y (i, j) + *f (
F) ...(5-A)YE (i,
j)=y (i, j)
...(5-B) F= (4*Y (i, D −
Y (i-1, j-1) -Y (i+l, j-1)
Y (i-1, j+1) -Y (i+l, j+1)
) /4 ... (5-C) By performing edge enhancement in this way, it is possible to suppress the expansion of variations in each color, which was a problem in the past, and the edges of black text become sharper, making it possible to Even parts that were crushed can be clearly reproduced.

Figure 3(a) is a diagram showing black letters written on paper.
Figure (b) shows the density distribution of a cross section of black characters read by the scanner. An image read from a scanner usually has smooth edges as shown in FIG. 3(b). When this is binarized using a fixed threshold value T (=50), the result is as shown in FIG. 3(C), and when this is subtracted from the original image, the result is as shown in FIG. 3(d). As can be seen from the hatched area in FIG. 3(d), edges are generated again in the image from which the black characters have been removed, and when this is orthogonally transformed encoded, the encoding efficiency is significantly reduced. Third
The edge portion in Figure (d) is an unnecessary portion from the perspective of image quality, and one of the features of this embodiment is to remove this portion from the color image and replace it with the average value of the pixel values within the block. It has become. In other words, by replacing the peripheral part of a black character with the average value within the block, the undulations within the block can be reduced, and the encoding efficiency when performing orthogonal transformation can be improved. Note that the replacement is not limited to the average value, but it is also possible to replace it with the most frequent value or replace it with the median value of the pixels in the block using a median filter.

FIG. 4(a), FIG. 4(b), and FIG. 4(c) are diagrams for explaining the operation of the achromatic color determination section 19. Figure 4 (a
) indicates the black text stored in the frame memory 17, and * indicates the pixel of the black text of interest. The 3×3 box centered on * is the achromatic color determination area when * is the pixel of interest. The shaded area in Figure 4(b) is the area where the * pixel is actually the pixel of interest and is determined to be achromatic with respect to the original image, and the shaded area in Figure 4(C) is the area where the final black character is determined. and the area that is determined to be an achromatic part around it. To obtain this decision area signal, an OR within the 3x3 block is taken. That is, if there is at least one achromatic pixel within a 3×3 block including the pixel of interest, the pixel of interest is determined to be an achromatic portion. The shaded area in FIG. 4(C) will be stored in the frame memory 20. Here, the block size is limited to 3x3, but may be 5x5.7x7.

FIG. 5 is a diagram for explaining the black character removal/average value replacement section 21. As shown in FIG. As shown in FIG. 5, for example, it is assumed that a black character in a certain block and its surrounding achromatic portion (the filled portion of the square) are stored in the frame memory 2o. For example, in Figure 5, black (filled pixels are 1
There are 0 pixels, and the black character removal/average value replacement unit 21
These 10 pixels are replaced with the average value of the remaining 6 pixels in the block. That is, the average value of the Y signal, the average value of the Cr signal, and the average value of the cb multiplied signal of 6 pixels corresponding to the white part in FIG. Cr signal becomes CB signal. This process will be explained using the flowchart shown in FIG.

First, for each pixel of black character data stored in the frame memory 17, an achromatic color determination is performed for eight neighboring pixels of that pixel (Sl). This determination is made based on whether equations (3) and (4) are simultaneously satisfied. If the determination is that the color is achromatic, "1" is written in the corresponding position of the frame memory 20 (s2). However, as an initial state, the contents of the frame memory 2o are all "0". After completing the above processing for all pixels, next
The original data (frame memory 13) and the data in the frame memory 20 are taken in blocks of XN (N-4) (S4). For pixels whose value is "0" in the captured data of the frame memory 20, calculate the average value of each of Y+Cr and Cb (S
5). Then, for the pixel that is "1" in the captured data of the frame memory 20, Y, Cr, and
The average value of each Cb is used as data for that pixel and stored in the frame memory 22 (S6). Then, the above steps S4 to S6 are repeated for all blocks until the processing is completed. As a result of the above processing, the frame memory 22 stores values replaced by average values for the portions corresponding to black characters, and original data values for other portions. It turns out.

Next, the processing in the orthogonal transform encoding unit 23 will be explained.

For image data (frame memory 22) in which black characters and surrounding achromatic parts are replaced with the average value within the block,
The orthogonal transform encoding unit 23 performs two-dimensional discrete cosine transform of the 4×4 block to obtain its transform coefficients. At this time, the Y signal is directly subjected to orthogonal transformation using a 4×4 block, and the Cr.

For the cb acid component, in order to increase compression efficiency, take the average value within 2 × 2 blocks, subsample each to 1/2, and divide the subsampled data into new 4 × 4 blocks. , performs orthogonal transformation. Here, only the color components (Cr, Cb) are subsampled because their deterioration is less noticeable to human vision than the luminance component (Y).

The obtained transform coefficients are quantized using, for example, a quantization table as shown in FIG. 7(a). - As an example, the conversion coefficients obtained by converting the original data are shown in Figure 7(b).
The coefficients quantized according to FIG. 7(a) are shown in FIG.
Shown in Figure (c).

Specifically, each of the transform coefficients in FIG. 7(b) is divided by the corresponding component of the quantization table in FIG. 7(a) on the matrix, and the fractions below the decimal point are rounded down.
The quantized data shown in C) is obtained. Orthogonal transform encoding is performed by zigzag scanning the quantized coefficients as shown in FIG. 7(C), and performing Huffman encoding, and is sent to the encoded data transmitter 24 as encoded data.

Note that the above procedure can also be performed by computer software based on the flowchart of FIG.

In the encoded data transmitter 24, the black character pattern code is first transmitted, and then the Y, Cr, and Cb code data are transmitted in sequence. Prior to transmitting each side, a flag indicating which component the data is is transmitted.

As described above, by encoding the black character patterns together, the quality of the black characters can be maintained, and when separating the black characters from the original data, the black character parts, including the surrounding parts, are averaged within the block. By replacing it with a value, the efficiency of orthogonal transform encoding can be improved.

FIG. 9 is a block diagram of a portion that decodes encoded data.

The pattern code of the code data received by the code data receiving unit 31 is decoded as black character pattern information by the black character pattern decoding unit 33 and stored in the frame memory 35.

On the other hand, the orthogonal transform code is decoded in the orthogonal transform decoding section 32 using a procedure completely opposite to that of encoding. That is, first, the quantized transform coefficient information is decoded, and then the transform coefficient is multiplied by each component of the same quantization table as in FIG. figure)
. A two-dimensional inverse discrete cosine transform is applied to this image, and the resulting image is stored in the frame memory 34. Y, Cr,
After all the Cb data is collected, since the Cr and Cb data have been subsampled to 1/2, simple interpolation, linear interpolation, etc. are used to restore the data size to the same as the original data. And for each pixel Y
, Cr, Cb data, YCrCb-RGB
The conversion unit 36 restores each pixel to R, G, and B data. This conversion is shown in equation (6).

The pixel values in the black text portion of the restored data are replaced with the average value within a given block, but
The synthesis section 37 sets the level to zero according to the black character data read out from the frame memory 35. In other words, for pixels in the black text area, the values of other color components R, G, and H are set to zero, and
Make it completely black. r, g, which have undergone such processing
b data is sent to the image output section 38. On the other hand, 1-bit black character data is simultaneously sent to the image output section 38 as 1-bit BK data.

The image output unit 38 is, for example, a laser beam printer,
Consists of inkjet printers, thermal printers, dot printers, etc. When printing, press r+
g+ t) RGB-MMC conversion is performed on the data, but since the pixels in the black text part are R = G = B = 0, Y = M = C = 0, and UCR has already been realized. This has a particularly excellent effect in that procedures necessary for normal color hard copying such as , OCR, and inking can be omitted.

That is, when making a hard copy, if the signal of the black character pattern is used as the black signal, the black character can be processed in a single black color without any extra processing, and the quality of the black character is improved. According to the example, luminance (Y)
By using a signal to emphasize the edges of only achromatic parts without disturbing the color balance, it is possible to sharply reproduce the details of black characters that are scanned at the time of image input, which improves the detection accuracy of black character patterns. improves.

Furthermore, according to this embodiment, the black character part of the input image is detected and encoded separately, so first, the edge part of the image, especially the black character part, is patterned and encoded separately from the gradation image part. By doing so, encoding efficiency can be improved while maintaining high quality. In other words, orthogonal transform encoding, which is suitable for encoding grayscale images, is used for grayscale images. By applying an entropy code to the pattern, ringing can be prevented and the black text portion can be reproduced with high quality.

Second, in addition to the black text area, the achromatic areas surrounding the black text area are also lI! ! By scraping the 1m image and replacing it with the average value within the block, the efficiency of orthogonal transform encoding is greatly improved, and encoding can be performed using less data than in the case of only orthogonal transform encoding.

Furthermore, thirdly, by using the pattern information of the black text part as it is as a black signal, the black text part can be converted into Y or M.

The color shift that occurs when printing can be prevented by the combination of C colorants, and the circuit configuration can be simplified by omitting the step of installing UCRX, which is normally required for color hard copies. This is particularly effective for copying machines, for example.

In this way, according to this embodiment, excellent effects that cannot be obtained by orthogonal transform coding alone can be obtained.

In the above embodiment, address control for writing and reading from each frame memory is performed by a CPU (not shown).

Furthermore, the numerical values given in this example are not limited to those values.

In addition, the image input unit is not limited to a CCD line sensor.
It is an interface that inputs image output from a TV camera, still video camera, or computer using a CCD area sensor, etc., and is good quality.

In addition, the input color component signals are not limited to RGB, but also YMC.
, L*a*b*, YIQ, YUV, etc.

Further, the configuration of the black detection section 15 is not limited to the above embodiment. For example, as another method of black detection, there is also a method of directly using RGB signals. In this case, the design may be made to satisfy the following conditions.

(1) Overall level is low.

R, G, B<Ty (Ty=50) (2) The level difference between each color of R, G, and B is small (close to achromatic color).

R−G l <Tc (=30) G−B<Tc BR<Tc However, here, Ty250. Although Tc=30,
The values of Ty and Tc are not limited to these.

Furthermore, in the above embodiment, when performing orthogonal transform encoding, the luminance component Y and the chromaticity components Cr and Cb were converted, but the same effect can be obtained by converting the luminance component tree and the chromaticity components a-tree and b-tree. The effect of this can be obtained.

Alternatively, subsampling of the chromaticity component may be omitted and orthogonal transform coding may be performed as is, or orthogonal transform coding may be performed separately for each of the R, G, and B color components.

Further, the orthogonal transform is not limited to DCT, and Hadamard transform, discrete sine transform, etc. may be used.

Furthermore, the encoding of the black character part pattern is MH, MR.

Anything suitable for binary data encoding, such as MMR or static or dynamic arithmetic codes, can be used.

Further, although the encoded data transmitter sends the encoded pattern for one screen and then performs orthogonal transform encoding in the order of Y, Cr, and Cb planes, the order of transmission of each plane is not limited to this.

In addition, Y, Cr, and Cb are orthogonally transformed encoded in parallel,
The Y, Cr, and Cb components and the encoding pattern may be transmitted in parallel. In this case, the frame memory can be omitted and the circuit configuration becomes simple.

In addition, in the above-mentioned embodiment, edge emphasis was performed only on the luminance component, but as shown in FIG. Separately provided,
Edge enhancement can also be performed on all components including chromaticity components by making a decision using the Cr and Cb multiplied signals before edge enhancement and sending the decision signal to the black detection section 15. .

Based on a similar idea, edge enhancement may be applied to R, G, and B signals.

Further, although the description has been made using black characters as a typical example of the black line drawing area, it goes without saying that the black characters are not limited to characters, and include black thin lines.

Further, the black line drawing portion may be a line drawing portion having a slightly different color, such as dark blue or gray, for example.

〔Effect of the invention〕

As described above, according to the present invention, image data can be efficiently compressed while suppressing deterioration of image quality.

[Brief explanation of drawings]

FIG. 1 is a block diagram of the encoding section of the image encoding device according to the embodiment of the present invention. FIG. 2 is a diagram for explaining the operation of the edge enhancement section. FIG. 3 is an image read from the scanner. FIG. 4 is a diagram showing how the achromatic portion around the black character portion is detected. FIG. A diagram showing an example. Figure 6 is a flowchart showing the flow of achromatic color determination around black characters and average value replacement. Figure 7 is an example of a quantization coefficient, a conversion coefficient, and the result of quantizing the conversion coefficient. FIG. 8 is a flowchart showing the algorithm of orthogonal transform encoding; FIG. 9 is a block diagram of the decoding unit of the image encoding device according to the embodiment of the present invention; FIG. 10 is the diagram shown in FIG. It is a figure which shows the coefficient which dequantized the coefficient part of (c). 12... Edge emphasis unit 15... Black detection unit 18... Arithmetic coding unit 19... Achromatic color determination unit 21... Black character removal/average value replacement unit 23... Orthogonal transformation coding unit慴0(α) Diagram (b) Eagle diagram (C) Flute diagram (/)

Claims (7)

[Claims] (1) A means for detecting a black line drawing part of input image data, a means for expanding the black line drawing part, a black line drawing part detected by the black line drawing part detecting means, and a part other than the black line drawing part,
An image encoding device characterized by having encoding means that performs different encodings. (2) The image encoding apparatus according to claim 1, wherein the black line image detection means detects the black line image by edge determination and color component determination. (3) The image encoding device according to claim 1, wherein the expansion means expands the black line drawing portion in accordance with determination of pixel color components around the pixel of interest. (4) The portion other than the black line drawing portion is obtained by replacing the input image data of the portion corresponding to the pattern obtained by the expansion means with an average value of surrounding image data. The image encoding device described in Section 2. (5) The image according to claim 1, wherein the encoding means performs orthogonal transformation encoding on a portion other than the black line drawing portion, and performs other encoding on the black line drawing portion. Encoding device. (6) The image encoding device according to claim 1, wherein the encoding means encodes the black line drawing portion as binary pattern data, and encodes the other portions as multivalued data. . (7) means for detecting a line drawing portion of input image data; means for expanding the line drawing portion detected by the detecting means; and replacing the line drawing portion expanded by the expanding means in accordance with the values of surrounding image data. and means for encoding image data replaced by the replacing means.