JP2001111840A - Image compression method, image compressor and image input device - Google Patents

Abstract

PROBLEM TO BE SOLVED: To provide an image compressor that can efficiently compress a binary image compressing the binary image in a way of fixed length multi-value image compression with a prescribed code length and variable length binary image compression, comparing code lengths of the image after both compression methods and selecting either of the compressed codes which is shorter in the code length. SOLUTION: A bit converter 1 adds 7-bits whose value is '0' as the low-order bits of a binary image to convert the binary bit into 8 bits (the value is 0 or 255). A fixed length compressor 2 compresses (JPEG) the 8-bit image and stores the image to a buffer 3. A variable compressor 4 compresses the binary image by the MH or the MMR or the like and stores the compressed image to a buffer 5. Whether or not the code length exceeds a prescribed byte is checked in this case, and the buffer 5 outputs a decision signal to a selector 6. The selector 6 outputs a code in the buffer 3 when the code length exceeds the prescribed byte or outputs a code in the buffer 5 when the code length does not exceed the prescribed byte.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an image compression method, an image compression apparatus, and an image input apparatus, and more particularly to an image input apparatus having a limited capacity storage apparatus such as a digital camera, which contributes to saving of storage capacity. The present invention relates to a compression method and an image compression device for realizing the compression method.

[0002]

2. Description of the Related Art With the development of video cameras and digital still camera devices that have been exclusively used as video input devices, there has been an increasing demand for using them as document input devices. In particular, recent digital still cameras have begun to be used for various purposes as portable information collection tools due to the increase in pixels and miniaturization. For text information such as documents, signs, advertisements, etc., sufficient information can be obtained by a binary image, and the storage capacity required for storage is small. Therefore, it is advantageous to store the information as a binary image. Further, the binarized image can be transmitted by facsimile or can be reused by character recognition. Further, when a CCD of 3 million pixels class is used, 375 kilobytes are required even if a multi-valued color image (YUV 4: 2: 2) is reduced to 1/16 by JPEG compression.

On the other hand, if the image is a black and white binary image, 3
If a binary image such as MH or MMR is compressed at 75 kilobytes, sufficient compression can be expected for an image mainly composed of characters.

[0004]

However, when an image such as a natural image is binarized using pseudo halftone processing such as dithering or error diffusion, the code length after MH or MMR compression becomes smaller than the image size before compression. Often it becomes larger and there is no point in compressing. In JBIG, in principle, the image size does not become larger than the image size before compression, but the calculation is complicated, and the compression ratio is not significantly improved with respect to the pseudo halftone image.

[0005] The present invention has been made in view of the above circumstances, and an object of the present invention is to compress a binary image.
Perform fixed-length multi-level image compression and variable-length binary image compression to compress to a predetermined code length, compare the code lengths after compression by both compressions, and select the code with the shorter code length, To provide an image compression method and an image compression apparatus for efficiently compressing image data.

Another object of the present invention is to provide an image input device capable of storing as many black and white binary images as possible using the compression device of the present invention.

[0007]

According to the present invention, a binary image is converted into 8 bits (0 or 255 values) by adding 7 bits having a value of 0 to the lower part of the binary image, and is converted to 8 bits by a fixed length compressor. Compress the image. In addition, the binary image is compressed by the variable length compressor,
At this time, it is checked whether the code length has exceeded a predetermined byte.
If it exceeds a predetermined byte, a code compressed by a fixed length compressor is selected, and if not, a code compressed by a variable length compressor is selected.

In the case where the present invention is applied to an image input apparatus, an encoded length obtained by binarizing a fetched multi-valued image and then compression by a fixed-length compressor and compression by a variable-length compressor are used. The lengths are compared, and the shorter code is selected and stored.

[0009]

DESCRIPTION OF THE PREFERRED EMBODIMENTS One embodiment of the present invention will be specifically described below with reference to the drawings. (Embodiment 1) FIG. 1 shows the configuration of Embodiment 1 of the present invention.
In the figure, 1 is a bit converter, 2 is a fixed length compressor, 4
Is a variable length compressor, 3 and 5 are buffers, 6 is a selector, and 7 is a code length discrimination signal.

[0010] The binary image is input to the variable length compressor 4. In the variable length compressor 4, compression such as MH or MMR, which is a known binary image compression method, is performed. MH and M
MR has the advantages that the calculation is simple and easy to realize, and that the compression speed is high. In particular, since the compression method is optimal for character images, a high compression ratio can be obtained for document images. For example, in an image having a size of 1280 × 960, the code size of MH and MMR is about 20 kbytes to 3 while the image size of an uncompressed binary image is 154 kbytes.
0 kbytes. In the case of a binary image subjected to pseudo halftone processing, both the MH and the MMR become large when the code length after compression is larger than the image size before compression.

The binary image is converted by the bit converter 1 into 8 bits by adding 7 bits having a value of 0 to the lower bits. The value of the image converted to 8 bits is 0 or 255
Is one of The 8-bit image is compressed by the fixed-length compressor 2. The fixed-length compressor 2 uses a well-known JPEG
Compression is performed. JPEG compression is originally a multi-valued image compression method for an 8-bit color image.
If 1 and 1 are assigned to luminance 0 and 255 and the color component is set to 0, application to a binary image is possible. The code length after JPEG compression is set to about ／ of the image size of the uncompressed binary image. For example, if the size of the image is 1280 × 96
If it is 0, the image size of the uncompressed binary image is 154
kbytes. If the image compression ratio is set to 2/3, J
The code length after PEG compression is 100 kbytes. About 1
If it is 00 kbytes, even if the JPEG image is decoded and binarized again, the deterioration is not so noticeable as compared with the binary image before encoding.

Codes encoded by the variable length compressor 4 and the fixed length compressor 2 are temporarily stored in buffers 5 and 3, respectively. The variable length compressor 4 outputs to the selector 6 a determination signal 7 indicating whether or not the code has exceeded 100 kbytes. Selector 6
Receives the determination signal 7 of the variable length compressor 4 and receives 100 kby
te (that is, the code length of the variable-length coding is longer than the code length of the fixed-length coding), the code of the buffer 3 does not exceed 100 kbytes (that is, the variable-length coding). Is shorter than the code length of the fixed-length coding).

(Embodiment 2) FIG. 2 shows the configuration of Embodiment 2 of the present invention. FIG. 2 is a diagram showing a configuration from image input of the digital still camera to binarization compression storage of a luminance signal.

The CCD 11 is a means for converting light condensed through the optical system into an electric signal.
Output an analog image signal. The AGC circuit 10
This is a circuit that electrically amplifies the signal output from the CD. In the case of shooting where the amount of exposure is insufficient, such as when the brightness of the subject is insufficient and the shutter speed cannot be slowed, increase the gain and output an appropriate level. Is obtained. The output image signal is converted into a digital signal by the A / D converter 12. The digital signal is sent to the white balance adjuster 1
At 3, the white balance is adjusted. White balance adjustment detects an achromatic part in an image, and the achromatic color is R = G
= B is adjusted for each color signal.

Next, a luminance signal is generated by a luminance signal generating means in which the luminance signal generator 14 and the luminance signal selector 15 are combined. The luminance signal generator 14 generates two luminance signals for the image whose white balance has been adjusted. One is a broadband luminance signal and the other is a narrowband luminance signal. The broadband luminance signal YH is calculated by the following equation when the target pixel is R, G, and B, respectively. YH_R = R YH_G = G YH_B = B When the subject is monochrome, a luminance signal with the widest band is generated.

Next, for the narrow band luminance signal YL,
For example, when the RGB filters are arranged in a checkered pattern as shown in FIG. 3, the YL signal in G0 is generated as in the following equation. YL_G0 = (4G0 + G1 + G2 + G3 + G4) / 8 Further, the YL signal in R0 and B0 is generated as in the following equation. YL_R0 = (G0 + G1 + G2 + G5) / 4 YL_B0 = (G0 + G1 + G3 + G6) / 4

As described above, using the surrounding G pixels,
By taking the average, a narrow-band luminance signal YL with little noise is generated. The luminance signal selector 15 outputs an Ev value calculated from the aperture amount and the shutter speed of the camera to obtain a proper exposure and a preset value Ev0 (f-value of the lens when the aperture is opened and a shutter speed that is slow enough to prevent camera shake. If the Ev value is greater than Ev0, YH is selected, and if the Ev value is equal to or less than Ev0, YL is selected and output.

However, in actual shooting, the shutter speed is set to 1 / focal length (mm) second at the latest in order to prevent camera shake even without using a flash.

The generated luminance signal is supplied to an aperture corrector 1
In step 6, the outline of the image is corrected. FIG. 4 shows a detailed configuration of the aperture corrector. For the luminance signal, the Laplacian in the vertical direction and the Laplacian in the horizontal direction are calculated by the Laplacian filters 31 and 32 in the vertical and horizontal directions. The absolute values 33 and 34 of the Laplacian in the vertical direction and the horizontal direction are compared by a comparator 35, the Laplacian having the larger absolute value is selected by a selector 36, and an adder 37 adds it to the original luminance signal.

As shown in FIG. 5, the coefficient of the Laplacian filter is a high-pass type shown in FIG. 5 (a) when the exposure value Ev is larger than a predetermined value Ev0.
The band-pass filter of (b) is used. The coefficient of the filter is stored in the parameter 38, and the coefficient (a) or (b) of the filter is changed to the filter 31,
32 is set. If the bandpass type is used, fine noise of one dot is suppressed, and when the brightness of the subject is insufficient, not only the noise of the background is reduced but also the quality of characters is improved.

Next, the luminance signal subjected to the aperture correction is binarized. The aperture corrected luminance signal is stored in the temporary frame memory 17. Since the image size is determined by the size of the CCD 11, the CP is determined based on the image size.
U18 calculates the block size and the sampling period required for the binarization processing, and controls the block buffer 19 and the non-low luminance pixel average value calculator 20, respectively.

FIG. 6 is a diagram showing a sampling cycle. FIG. 6A shows a case where the image size is small.
Indicates a sampling period when the image size is large.
The unevenness in brightness of an image captured by a camera is bright near the center of the image and becomes darker toward the periphery. Accordingly, if the shape of the block division of the image is stored in advance in the ROM of the CPU 18 as a combination of a square, a rectangle, and a triangle as shown in FIG. It is more uniform and enables higher quality binarization as compared to using only square blocks.

The block buffer 19 is a buffer for reading an image from a frame memory and temporarily storing the image in units of blocks of a predetermined shape and size. The non-low-brightness pixel average value calculator 20 is a means for sampling and reading out the pixels from the image stored in the block buffer 19 at a preset sampling period, and calculating the average of the brightness values.

FIG. 8 shows a detailed configuration of the non-low luminance pixel average value calculator. The sampled pixel value is compared with the threshold value thl_ij by the comparator 41. As a result of the comparison,
If the pixel value is larger than the threshold value, the gate 45 is opened, the value of the addition result register 42 and the pixel value are added by the adder 46, and the result is stored in the addition result register 42. At the same time, the counter 43 is incremented by one. Here, as a result of the increment, as the result of the increment, when the digit goes up (the counter indicates a power of 2), the gate 47 is opened, the result of the adder is stored in the shift register 44, and the bit indicated by the counter is read. Shift right by a number. After processing for all the pixels in the block, the value stored in the shift register 44 becomes the non-low luminance pixel average value ave
_Ij.

The non-low-luminance pixel detection threshold value setting unit 21 adds a predetermined coefficient to the non-low-luminance pixel average value ave_i-1j of the previous block (if the current block is (i, j), it indicates (i-1, j)). The threshold value thl_ij used by the non-low-luminance pixel average value calculator 20 is calculated by multiplying Ca. The predetermined coefficient is Ca
= 1/4, non-low luminance pixel detection threshold value setting unit 21
Is a value excluding the lower two bits of ave_i-1j, so that a special circuit is not required. The binarization threshold value setting circuit 22 uses the ave_ij calculated by the non-low luminance pixel average value calculation circuit 20 to binarize a threshold value th_ for image binarization.
Set ij.

The binarization threshold setting circuit 22 calculates a predetermined coefficient C
b is a multiplier for multiplying ave_ij by Cb = x /
If 16 or Cb = x / 8 (x is a predetermined value representing a natural number not exceeding the denominator), the binarization threshold setting circuit 22 can be composed of only an adder, which is advantageous in terms of cost and speed. A binarizer 23 using a binarization threshold th_ij
Binarize the block with. The binarized image is subjected to image compression by the compressor 24.

FIG. 9 shows a detailed configuration of the compressor. The binarized image is supplied to the variable length compressor 51 and the fixed length compressor 5.
2 is input. The variable-length compressor 51 performs compression such as MH or MMR, which is a known binary image compression method. MH and MMR have the advantages that calculations are simple and easy to realize, and that the compression speed is fast. In particular, since the compression method is specialized for character images, a high compression ratio can be obtained for document images. For example, in an image having a size of 1280 × 960, the image size of an uncompressed binary image is 154 kbytes.
e, the code length of MH and MMR is about 20 kbytes.
３０30 kbytes. In the case of a binary image subjected to pseudo halftone processing, both the MH and the MMR become larger when the code length after compression is larger than the image size before compression.

The fixed-length compressor 52 performs known JPEG compression. JPEG compression is a multi-valued image compression method for an 8-bit color image originally.
Is assigned to luminance 0 and 255, and if the color component is set to 0, application to a binary image is possible. The code length after JPEG compression is set to about ／ of the image size of the uncompressed binary image. For example, if the size of the image is 1280 × 960
, The image size of the uncompressed binary image is 154 k
Byte. If the image compression ratio is set to 2/3, JP
The code length after EG compression is 100 kbytes. About 10
If it is 0 kbyte, even if the JPEG image is decoded and binarized again, the deterioration is at a level that does not matter as compared with the binary image before encoding.

The codes encoded by the variable length compressor 51 and the fixed length compressor 52 are temporarily stored in buffers 53 and 54, respectively. The variable length compressor 51 has a compressed code of 100 k
The determination signal 56 indicating whether or not the number of bytes has exceeded
5 is output. The code selector 55 receives the discrimination signal 56 of the variable length compressor 51, and if the code length exceeds 100 kbytes (when the code length of the variable length coding is longer than the code length of the fixed length coding), The code is 100 kby
If te does not exceed (the code length of the variable length coding is
The code in the buffer 53 is read out and output to the memory 25 in FIG. 2 (when the code length is shorter than the fixed-length code length), and the coded image is stored.

(Embodiment 3) FIG. 10 shows Embodiment 3 of the present invention.
Is shown. The difference from the second embodiment is that a pseudo halftone processing binarization circuit 27, a selector 28, and a mode setting unit 9 are provided. Processing until the aperture-corrected luminance signal is stored in the temporary frame memory 17 is the same as in the second embodiment.

The luminance signal subjected to the aperture correction is binarized as follows. The image is transferred from the frame memory 17 to the block buffer 19 as in the second embodiment. The image transferred to the block buffer 19 is input to the pseudo halftone processing binarization circuit 27 and the simple binarization circuit 23. The pseudo halftone processing binarization circuit 27 binarizes the image using pseudo halftone processing (known dither processing or error diffusion processing).

The block buffer 19, the non-low-luminance pixel average value calculator 20, the non-low-luminance pixel detection threshold setting unit 21, and the binarization threshold setting circuit 22 in the character binarization circuit 26 have been described in the second embodiment. The description is omitted because it is the same as that of FIG.

As in the second embodiment, the binarization threshold th_ij
Is used to binarize the block by the simple binarizer 23. The binary image subjected to the pseudo halftone processing and the binary image converted to the simple binary are input to the selector 28.

The mode setting unit 9 sets a character binarization mode or a natural image binarization mode of the camera. When the character binarization mode is set, a simple binary binarization mode is set. When the image is set to the natural image binarization mode, the binary image subjected to pseudo halftone processing is selected by the selector 28 and output. The selected image is compressed by the compressor 24 in the same manner as described in the second embodiment, and the encoded image is stored in the memory 25.

(Embodiment 4) FIG. 11 shows Embodiment 4 of the present invention.
Is shown. The difference from the third embodiment is that an image area separating circuit 30 is provided instead of the mode setting device.

The image transferred to the block buffer 19 as in the second embodiment is input to the image area separating circuit 30, the pseudo halftone processing binarizing circuit 27 and the simple binarizing circuit 23. The image area separation circuit 30 determines a character or non-character (picture) area for each pixel of the image.

FIG. 12 shows the details of the image area separation circuit 30. The image signal of the block buffer 19 and the output signal of the simple binarization circuit 23 are input to the image area separation circuit 30.
The input image signal is supplied to an edge extraction circuit 301, which is shown in FIG.
14 or a first derivative operation (the focused pixel is the center pixel of the left and right filters) as shown in FIG. 14 or a Laplacian operation having a mask coefficient as shown in FIG. By binarizing the calculated value edge with a predetermined threshold th, it is determined whether the pixel of interest is an edge or a non-edge.

The output signal of the simple binarization circuit 23 is
The boundary detection circuit 303 detects a boundary between white and black. The boundary detection circuit 303 determines that the target pixel is a boundary when both the white pixel and the black pixel are mixed in the 3 × 3 pixel including the target pixel, and determines that the target pixel is a white pixel in the 3 × 3 pixel. If only pixels or only black pixels exist, it is determined that the boundary is not a boundary.

The output of the binarization circuit 302 and the boundary detection circuit 3
By taking the logical product 304 of the outputs of the numbers 03, it is determined whether or not the pixel of interest is a character area (edge and boundary) (non-character area) and output to the selector 28.

Returning to FIG. 11, the pseudo halftone processing circuit 27
Then, the image is binarized using pseudo halftone processing (known dither processing or error diffusion processing).

The binary image subjected to the pseudo halftone processing and the binary image which has been simply binarized are based on the character / non-character discrimination signal of the image area separating circuit 30. In the case of a character area, the binarized image is simply binarized. If the value image is a non-character area, a binary image subjected to pseudo halftone processing is selected by the selector 28 and output. The selected image is transmitted to the compressor 24 in the same manner as described in the second embodiment.
, And the encoded image is stored in the memory 25. (Embodiment 5) Embodiment 5 of the present invention relates to an image compression method. FIG. 15 is a processing flowchart of the fifth embodiment. First, a binary image is input (step 101). The input binary image is converted into an 8-bit multi-valued image that takes only binary values of 0 and 255 (adds 7-bit 0 to the lower order), and is fixed for a multi-valued image at a predetermined compression ratio. Long encoding is performed (step 10).
2). A typical example of fixed-length encoding is JPEG.

Next, variable-length coding for the binary image is performed on the binary image (step 103). Representative examples of variable length coding are MH and MMR. The code lengths encoded by the respective encodings are compared (step 104).
If the code length of the variable length coding is short, a variable length code is selected (step 105), and if the code length of the fixed length coding is short, a fixed length code is selected (step 106) and stored (step 107).

[0043]

As described above, according to the first and third aspects of the present invention, it is possible to compress a fixed-length multi-valued image having a simple configuration and a high compression rate onto a binary image. become.

According to the second and fourth aspects of the present invention, since different compression methods or different compression means are provided, it is possible to obtain a high compression rate and high quality image compression regardless of the contents of the binary image. It becomes possible.

According to the fifth aspect of the present invention, it is possible to obtain an image input device capable of storing a binarized image with high compression and high image quality when storing a captured image.

According to the sixth and seventh aspects of the present invention, when binarizing an image, the binarizing means can be switched in accordance with the type of the input image. can get.

According to the eighth aspect of the present invention, since the binarization method can be selected for each area according to the image area (character / non-character), a high quality binary image can be obtained.

[Brief description of the drawings]

FIG. 1 shows a configuration of a first exemplary embodiment of the present invention.

FIG. 2 shows a configuration of a second exemplary embodiment of the present invention.

FIG. 3 shows a pixel array of a CCD.

FIG. 4 shows a configuration of an aperture correction circuit.

FIG. 5A shows a high-pass type Laplacian;
(B) shows a bandpass type Laplacian.

FIGS. 6A and 6B show different sampling periods.

FIG. 7 shows a method of dividing an image into blocks.

FIG. 8 shows a configuration of a non-low luminance pixel average value calculator.

FIG. 9 shows a configuration of an image compressor.

FIG. 10 shows a configuration of Embodiment 3 of the present invention.

FIG. 11 shows a configuration of a fourth embodiment of the present invention.

FIG. 12 shows a configuration of an image area separation circuit.

FIG. 13 shows Laplacian mask coefficients.

FIG. 14 shows a first derivative operation.

FIG. 15 shows a processing flowchart of Embodiment 5 of the present invention.

[Explanation of symbols]

 1 bit converter 2 fixed length compressor 3, 5 buffer 4 variable length compressor 6 selector 7 code length discrimination signal

Claims (8)

[Claims] 1. An image compression method for compressing a binary image, comprising: converting the binary image into a multi-valued image; and compressing the multi-valued image to a predetermined code length. Characteristic image compression method. 2. An image compression method for compressing a binary image, comprising the steps of: converting the binary image into a multi-valued image and then compressing the binary image into a code of a predetermined length; An image compression method, comprising the steps of: comparing each code length after the compression; and selecting and outputting a code having a shorter code length. 3. An image compression apparatus for compressing a binary image, comprising: means for converting the binary image into a multi-valued image having a predetermined bit width; and means for compressing the multi-valued image to a predetermined code length. An image compression device comprising: 4. An image compression apparatus for compressing a binary image, comprising: means for converting the binary image into a multi-valued image having a predetermined bit width; and means for compressing the multi-valued image to a predetermined code length. 1
, A second compression unit that performs variable-length encoding on the binary image, and a code length after compression by the first and second compression units, and selects a code having a shorter code length. And an output unit for outputting the image. 5. An image input device for encoding and storing a multi-valued image, comprising: a unit for inputting the multi-valued image; a unit for binarizing the multi-valued image; A first compression unit for compressing to a code length, a second compression unit for variable-length encoding the binary image, and a code length after compression by the first and second compression units are compared. Means for selecting and storing the shorter code of the image input device. 6. The binarizing unit according to claim 5, wherein said binarizing unit comprises a first binarizing unit and a second binarizing unit which are selectively operated according to predetermined information. Image input device. 7. The image input device according to claim 6, wherein the predetermined information is character designation information or natural image designation information. 8. The image input device according to claim 6, wherein the predetermined information is an attribute for each area of the image.