JP2006352279A - Image processor and image processing method - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide an image processor and an image processing method in which deterioration in image quality due to ground removal processing for suppressing noise when an irreversibly compressed image is decompressed can be reduced suitably. <P>SOLUTION: The ground removing section in a printer image processing section 105 performs noise removal of image data which is irreversibly compressed at an image compressing section 102 and decompressed at an image decompressing section 104. A controller section 202 determines parameters during noise removal processing in correspondence with parameters utilized during irreversible compression. Ground removal processing for converting the pixel of substantially white level of decompressed image data into a pixel of white level is performed using the parameters thus determined and overlying part supplementation processing is performed at a supplementation section. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an image processing apparatus and an image processing method for reducing reduction in image quality when decompressing irreversibly compressed image data.

  In general, printing using a printer is performed by a mechanism in which a bitmap image is generated by RIP (raster image processing), and this is printed on a recording sheet or the like and output. The bitmap image can be generated by analyzing and generating the page description language included in the print job received from the host computer such as a PC, or by generating the luminance signal by reading the copy source document with a scanner. There is a way to do it.

  In recent years, high-definition printers have been developed, and bitmap images are generated at 600 dpi and 1200 dpi. Since the data size of the bitmap image generated by such a printer becomes very large, the memory in the printer system is consumed and the handling load increases. For this reason, when outputting a plurality of pages, memory and CPU resources are occupied for holding and handling the generated bitmap image. Therefore, execution of another process (for example, generation of a new page) in the printer may be executed after waiting for a state where the recording output is completed and the data amount of the corresponding bitmap image decreases. This is necessary and reduces the processing efficiency of the printer.

  In order to solve such problems, the generated bitmap image is temporarily compressed and stored in the memory, thereby reducing the memory consumption of the bitmap image and increasing the memory capacity available for other processing. It has been proposed to increase the processing efficiency of the printer.

  As a general compression method for still images as described above, there is a JPEG method using discrete cosine transform. However, since this JPEG method is an irreversible compression method, depending on the characteristics of the image and the parameters at the time of compression, there may be a case where the image is greatly deteriorated.

  For example, mosquito noise that is likely to occur at the edge portion of an image exists as one of the noises indicating image degradation. This mosquito noise is a noise that is likely to occur in a place with a lot of high frequency components such as an edge portion. As a method for suppressing such mosquito noise, there is a method of reducing the mosquito noise by performing filter processing corresponding to the compression rate on the decompressed image (see, for example, Patent Document 1).

However, the method shown in Patent Document 1 reduces the influence of mosquito noise by changing the spatial frequency of the image, and does not directly remove mosquito noise. As a method of directly removing mosquito noise, there is a method of applying a background removal process corresponding to the compression rate (see, for example, Patent Document 2). Here, the background is a portion having a luminance value close to the white level of the image.
JP 2001-2111318 A JP 2001-016452 A

  In the prior art as described above, the background removal is adaptively performed according to the compression rate as a method for removing mosquito noise, but this method is premised on the occurrence of image distortion according to the compression rate. . However, in the case of an image with few high-frequency components, there is a case where even if the conventional techniques as described above are used, there is little image degradation and a high compression rate can be achieved. When strong background removal processing is performed on such an image in accordance with the compression rate, the adverse effect of degrading the quality of the original image is greater than the effect of removing noise. In particular, in the gradation portion in the image, the gradation of the highlight portion is skipped by the background removal, and a pseudo contour is likely to occur.

  Further, mosquito noise appears on the image in such a manner that the luminance value of a pixel having a large luminance value at the edge portion decreases and the luminance value of a pixel having a small luminance value increases. However, in the conventional method in which only the background removal is performed, although the influence of the decrease in the luminance value of the pixel having the large luminance value can be removed, the luminance of the pixel having the small luminance value is increased. It has not been taken into account and cannot be adequately addressed.

  The present invention has been made in consideration of such circumstances, and it is possible to suitably reduce image quality degradation due to background removal processing that reduces noise when an irreversibly compressed image is expanded. An object of the present invention is to provide an image processing apparatus and an image processing method.

In order to solve the above problems, an image processing apparatus according to the present invention provides:
Compression means for irreversibly compressing image data;
Storage means for storing the image data compressed by the compression means;
Decompression means for decompressing the image data stored in the storage means;
Determining means for determining a parameter at the time of noise removal processing of the image data decompressed by the decompressing means, corresponding to a parameter used at the time of irreversible compression of the image data by the compressing means;
Noise removal means for performing noise removal processing on the image data decompressed by the decompression means using the parameters determined by the determination means.

In order to solve the above-described problem, an image processing method according to the present invention includes:
A compression process for irreversibly compressing image data;
A storage step of storing the image data compressed in the compression step in a storage means;
A decompression step of decompressing the image data stored in the storage means;
A determination step for determining a parameter at the time of noise removal processing of the image data decompressed by the decompression step in response to a parameter used at the time of irreversible compression of the image data by the compression step;
A noise removal step of performing a noise removal process on the image data decompressed in the decompression step using the parameter determined in the determination step.

  According to the present invention, it is possible to suitably reduce image quality deterioration due to the background removal processing that reduces noise when an irreversibly compressed image is expanded. According to the present invention, in particular, it is possible to suitably suppress the shading of the pseudo contour and the shadow portion generated by the background removal process for removing mosquito noise.

  Hereinafter, embodiments according to the present invention will be described in detail with reference to the drawings.

<First Embodiment>
FIG. 2 is a schematic block diagram of the image forming apparatus 200 according to the first embodiment of the present invention. In this embodiment, as the image forming apparatus 200, a digital multifunction peripheral having a function such as a general COPY / PRINT / FAX is used. As shown in FIG. 2, the image forming apparatus 200 according to the present embodiment includes a scanner unit 201 that performs document reading processing, and a controller unit 202 that performs image processing on image data read from the scanner unit 201 and stores the image data in a memory 205. And an operation unit 204 for setting various printing conditions for the image data read by the scanner unit 201, and the image data read from the memory 205 is visualized on a recording sheet according to the print setting conditions set by the operation unit 204. A printer unit 203 that performs image formation is provided. The image forming apparatus 200 is connected to a server 207 that manages image data, a personal computer (PC) 208 that instructs the image forming apparatus 200 to execute printing, and the like via a network 206 such as a LAN. Has been.

  FIG. 3 is a cross-sectional view of a digital multifunction peripheral that implements the image forming apparatus 200 according to the first embodiment. Next, a more detailed configuration of the image forming apparatus according to the present exemplary embodiment will be described with reference to FIG. As described above, the image forming apparatus 200 has a function such as COPY / PRINT / FAX. As shown in FIG. 3, the image forming apparatus according to the present embodiment includes a scanner 301, a document feeder (DF) 302, a print recording printer 313 including a four-color drum, a paper feed deck 314, a finisher 315, and the like. It has.

  First, a reading operation performed using the scanner 301 as a center will be described. When a document is set on the document table 307 and read, the user sets the document on the document table 307 and closes the DF 302. Then, after detecting that the document table 307 is closed by the open / close sensor 330, the light reflection type document size detection sensors 331 to 335 in the housing of the scanner 301 detect the set document size. Starting from this size detection, the light source 310 irradiates the document, and a CCD (Charge-Coupled Device) 343 receives the reflected light from the document via the reflector 311 and the lens 312 and reads the image data.

  Then, the controller unit 202 of the image forming apparatus 200 converts the image data read by the CCD 343 into a digital signal, performs desired image processing, and converts it into a laser recording signal (hereinafter simply referred to as “recording signal”). Convert. The converted recording signal is subjected to image processing which will be described later with reference to FIG.

  When a document is set on the DF 302 and read, the user places the document face up on the tray of the document setting unit 303 of the DF 302. Then, the document presence / absence sensor 304 detects that the document has been set, and in response to this, the document feed roller 305 and the conveyance belt 306 rotate to convey the document, and the document is detected at a predetermined position on the document table 307. The original is loaded. In the subsequent processing, the image data is read in the same manner as the reading processing on the document table 307 described above, and the obtained recording signal is subjected to the image processing described with reference to FIG. It is stored in the memory 205 in the unit 202.

  After the reading of the image data is completed, the conveying belt 306 rotates again, and the document is sent to the right side in the cross-sectional view of the image forming apparatus shown in FIG. Documents are discharged to the tray 309. If there are a plurality of documents, the documents are discharged from the document table 307 to the right side in the sectional view of the image forming apparatus, and at the same time from the left side in the sectional view of the image forming apparatus via the sheet feeding roller 305. The next original is fed, and the next original is continuously read. The above is the operation of the scanner 301.

  Next, a printing operation performed using the printer 313 as a center will be described. The recording signal (print image data) once stored in the memory 105 in the controller unit 202 is subjected to image processing described with reference to FIG. 1 to be described later, transferred to the printer 313, and recorded by the laser recording unit. Converted to laser light. Then, the recording laser light is irradiated to the photoconductors 316 of the respective colors, and an electrostatic latent image is formed on each photoconductor. The printer 313 performs toner development on each photoconductor with the toner supplied from the toner cartridge 317, and the toner image visualized on each photoconductor is primarily transferred to the intermediate transfer belt 321. The intermediate transfer belt 321 rotates clockwise in the cross-sectional view shown in FIG. 3, and the recording paper fed from the paper cassette 318 or the paper feed deck 314 through the paper feed conveyance path 319 reaches the secondary transfer position 320. At this point, the toner image is transferred from the intermediate transfer belt 321 to the recording paper.

  The recording paper onto which the image has been transferred is fixed with toner by pressure and heat by the fixing device 322 and is conveyed through the paper discharge conveyance path, and then is discharged to the finisher by face-down center tray 323 or switch back. The paper is discharged to the paper outlet 324 or the face-up side tray 325. The side tray 325 is a paper discharge port that can discharge paper only when the finisher 315 is not installed. The flappers 326 and 327 are for switching the transport path in order to switch these discharge ports.

  In the case of double-sided printing, after the recording paper passes through the fixing device 322, the flapper 327 switches the conveyance path, and then switches back to send the recording paper downward, and again through the double-sided printing paper conveyance path 330. The paper is fed to the secondary transfer position 320 and double-sided printing is performed.

  Next, the operation performed by the finisher 315 will be described. The finisher 315 performs post-processing on the printed paper according to the function designated by the user. Specifically, it has functions such as stapling (for example, binding at one place and two places), punching (for example, two holes, three holes), and saddle stitching. The image forming apparatus shown in FIG. 3 has two paper discharge trays 328, and the recording paper that has passed through the paper discharge port 324 to the finisher 315 is discharged for each copy / printer / fax function, for example, according to user settings. The paper tray 328 is sorted.

  The print engine 313 is a color 4-drum printer, but needless to say, may be a color 1-drum engine or a monochrome recording printer engine. When the image forming apparatus shown in FIG. 3 is used as a printer, black and white printing / color printing, paper size, 2UP / 4UP printing / N-UP printing, duplex printing, stapling, punching, bookbinding saddle stitching, and slip sheets are performed by a driver. Various settings such as front cover and back cover can be made.

  FIG. 1 is a block diagram illustrating a detailed configuration of a controller unit 202 that performs image processing of the image forming apparatus 200 illustrated in FIG. 2. Image processing performed by the above-described image forming apparatus 200 will be described with reference to FIGS.

  An image signal input from the scanner unit 201 is input to the controller unit 202. Examples of input image signals include signals of three colors of red (R), green (G), and blue (B), and 256 gradations, but are not limited thereto. The input image signal is subjected to known image processing such as shading correction, CCD line correction, color correction, and sharpening of black characters in the scanner image processing unit 101.

  The image compression unit 102 is a block that compresses image data in order to store the image data in the memory 103 (corresponding to the memory 205 in FIG. 2), and is an irreversible compression method (in this embodiment, the JPEG method). ) Compresses and encodes the image signal. In the present embodiment, compression encoding is performed by performing discrete cosine transform (DCT transform), which is a known spatial frequency transform, in units of 8 × 8 pixels, quantizing DCT coefficients using a set quantization matrix, and performing quantization This is done by Huffman encoding the value. In compression encoding, RGB signals may be converted into luminance color difference signals (YCbCr) and then compressed.

  In general, since image degradation occurs due to quantization errors, the degree of image degradation is closely related to the quantization matrix used for quantization. By using this relationship, it is possible to adaptively switch parameters such as background removal processing in the printer image processing unit 105 described later. In this embodiment, RGB signals are used for input to the image compression unit 102, but CMYK signals may also be used.

  The compressed image is temporarily stored in the memory 103. The memory 103 is a storage medium and may be a semiconductor storage element or a hard disk. The compressed image data stored in the memory 103 is decompressed by the image decompression unit 104. The decompression process is performed by performing Huffman inverse coding on the compressed image data, returning the DCT coefficient value to the set inverse quantization matrix, and then performing a discrete cosine inverse transform (DCT inverse transform) process. Then, if the decompressed image signal is an RGB signal converted into a luminance color difference signal, it is converted into an RGB signal. In the present embodiment, the input to the image compression unit 102 is an irreversibly compressed RGB signal, but it may be a CMYK signal.

  The printer image processing unit 105 performs various processes on the image data expanded by the image expansion unit 104 and outputs the processed data to the printer unit 203. Next, processing of the printer image processing unit 105 will be described. FIG. 4 is a block diagram illustrating a detailed configuration of the printer image processing unit 105 in the controller unit 202 that performs various types of image processing in the image forming apparatus 200 according to the first embodiment illustrated in FIG. 2.

  For the image data expanded by the image expansion unit 104, the background removal unit 401 performs background removal processing based on the parameters used in the lossy compression. The background removal is an operation of pasting a portion (substantially white level portion) having a luminance value close to the white level, called a background portion of an image, to the white level. That is, in the case of RGB signals, the white level is 255. For example, the background processing is realized by converting the luminance value using a conversion table as shown in FIG.

  FIG. 5 is a diagram illustrating an example of a conversion table for background removal used by the background removal unit 401 of the printer image processing unit 105. In the conversion table shown in FIG. 5, which level of luminance value is pasted as a white level is a parameter for background removal processing. For example, in the example shown in FIG. 5, pixels with an input luminance area of 240 or more are set to the white level. Note that the content of the background removal processing is arbitrary, and is not limited to only using the conversion table shown in FIG.

  FIG. 6 is a diagram illustrating another example of the conversion table for background removal used in the background removal unit 401 of the printer image processing unit 105. As the conversion table, for example, as shown in FIG. 6, non-linear conversion processing other than the portion to be converted to the white level may be performed and pasted.

  As described above, the background removal process is a process capable of skipping mosquito noise in an image, but may have an adverse effect of destroying a highlight portion of the image. Therefore, selection of the background removal parameter is very important. Therefore, in the present embodiment, the selection of the background removal parameter is adaptively performed based on the parameter used in the lossy compression, so that the reduction of mosquito noise is suitably realized while minimizing the influence on the image.

  The parameters used in lossy compression include, for example, a quantization matrix used for compression. The main cause of image deterioration due to lossy compression is a quantization error, and the quantization error has a strong correlation with a quantization matrix used for quantization. In other words, if the relationship between the quantization table to be used and the optimum parameters for the background removal processing is obtained experimentally and the background removal parameters can be switched using this relationship, the background removal processing corresponding to the image degradation is realized. can do.

  Here, there is a conventional example using an image compression rate as an index for estimating image degradation. However, the image compression rate is a value that depends on two main factors: the degree of image degradation and the complexity of the image, and it is not appropriate to estimate the image degradation from this value. The compression rate is not a parameter used for lossy compression but an index obtained as a result of compression.

  In the printer image processing unit 105 shown in FIG. 4, the logarithmic conversion unit 402 and the color space conversion unit 403 convert the RGB signal, which is the luminance value after the background removal, into cyan (C) and magenta (M) as density values. , Yellow (Y) and black (K) CMYK signals. This is because the toner used when printing by the printer unit 203 is CMYK.

  The spatial filter unit 404 performs filtering by applying a known spatial filter that changes the frequency characteristics of the image. A gamma correction unit 405 performs gamma correction in accordance with the characteristics of the printer unit 203. As a result, there is an effect of preventing the density of the printed matter after printing from changing even with the same digital gradation according to the characteristics of the printer unit 203.

  The halftoning unit 406 converts the CMYK signal into the number of gradations that can be expressed by the laser of the printer unit 203. The conversion process at this time is a process of expressing a multi-value gradation in a pseudo manner. For example, an error diffusion process and a screen process are mentioned. The signal converted by the halftoning unit 406 is output to the printer unit 203. The subsequent processing is as described above.

  Processing for reducing irreversible compression in the image forming apparatus according to the present embodiment having the above-described configuration will be described with reference to a flowchart of FIG. FIG. 7 is a flowchart for explaining noise reduction processing in the image forming apparatus according to the first embodiment of the present invention.

  First, as described above, the image compression unit 102 performs irreversible compression, and the image data stored in the memory 103 is decompressed by the image decompression unit 104 (step S71). Next, a background removal parameter is determined based on a quantization matrix that is a parameter used for image compression by the image compression unit 102 (step S72). Note that the background removal parameter determination processing is performed by the controller unit 202, but information on the used quantization matrix can be obtained from the image compression unit 102, the memory 103, or the image expansion unit 104. It should be noted that the relationship between the quantization matrix and the background removal parameter is set in advance by a prior experiment or the like.

  Then, the printer image processing unit 105 performs background removal using the background removal parameter determined in step S72 (step S73). FIG. 8 is a diagram for explaining the effect of the noise reduction processing in the image forming apparatus 200. FIG. 8 schematically shows a change in luminance value of each pixel (pixel) in an image. The original image data shown in FIG. 8A is obtained from the results shown in FIGS. 8C and 8D by the background removal process using the background removal parameters described above after the lossy compression process and the decompression process. Become.

  As described above, it is possible to adaptively reduce mosquito noise by performing the background removal processing according to the image degradation described in the present embodiment.

<Second Embodiment>
In the image forming apparatus according to the second embodiment, a compensation unit is provided between the background processing unit 401 and the logarithmic conversion unit 402 of the printer image processing unit 105 of the controller unit 202 of the image forming apparatus 200 according to the first embodiment. Newly added. FIG. 9 is a block diagram showing a detailed configuration of the printer image processing unit 105 according to the second embodiment of the present invention. Note that the components other than the printer image processing unit of the image forming apparatus are the same as those in the first embodiment described above, and a description thereof will be omitted.

  In the printer image processing unit of the second embodiment shown in FIG. 9, the background removal unit 401, logarithmic conversion unit 402, color space conversion unit 403, spatial filter unit 404, gamma correction unit 405, and halftoning unit 406 are also included. This is the same as that of the first embodiment described above.

  In FIG. 9, a compensation unit 901 is a part that compensates for an upper portion that has changed due to image degradation due to lossy compression processing and decompression processing. Here, the top is a portion having a luminance value close to the black level of the image (substantially black level portion). As shown in FIG. 8, image degradation does not occur only in the background portion, but naturally occurs in the upper portion. Therefore, in this embodiment, in addition to the processing of the first embodiment described above, image deterioration is corrected by further compensating for the upper portion.

  Two methods are conceivable as means for compensating for image degradation. First, the first method is a method of performing compensation by pasting the upper portion to the black level. In the case of an RGB signal, the black level is 0. For example, it is realized by converting the luminance value in units of pixels using a conversion table as shown in FIG. FIG. 10 is a diagram illustrating an example of the conversion table for top surface compensation used in the compensation unit 901 of the printer image processing unit 905 according to the second embodiment.

  Here, what level of luminance value is pasted to the black level is a parameter of the first compensation method. In the present embodiment, the selection of the parameter is adaptively performed based on the parameter used in the lossy compression, thereby reducing the mosquito noise while minimizing the influence on the image. The parameters used in lossy compression include, for example, a quantization matrix used for compression. Further, in this method, the background removal and the ground filling can be performed simultaneously by integrating the conversion table for ground removal shown in FIG. 5 and the conversion table for ground filling shown in FIG. When this method is used, the background removal unit 401 and the compensation unit 901 can be combined into one processing unit.

  In the second method, processing is not performed on a pixel-by-pixel basis as in the first method described above, but the amount of compensation for the pixel of interest is determined from the background removal status of the surrounding pixels of the pixel of interest, and based on the amount of compensation This is a method to compensate.

  There is a strong correlation between the amount of change in the background portion of the image and the amount of change in the upper portion that occur due to lossy compression. That is, when the luminance value of the peripheral background portion decreases, the luminance value of the attention upper portion increases. Therefore, by considering the correlation and determining the top cover amount from the ground removal amount, there is a high possibility that an image closer to the image before irreversible compression can be restored. Specifically, a process of calculating the total amount of background removal for each DCT conversion processing unit (every 8 × 8 pixel unit) and compensating for a certain ratio in the upper part can be considered. In this case, the compensation ratio is a parameter. In the present embodiment, the selection of this parameter is adaptively performed based on the parameter used in the lossy compression, thereby minimizing the influence on the image and reducing the mosquito noise. As a parameter used in lossy compression, for example, there is a quantization matrix used in compression.

  Processing for reducing irreversible compression in the image forming apparatus of the present embodiment having the above-described configuration will be described. FIG. 11 is a flowchart for explaining noise reduction processing in the image forming apparatus according to the second embodiment of the present invention.

  First, the image data subjected to the irreversible compression by the image compression unit 102 is decompressed by the image decompression unit 104 (step S111). Next, a background removal parameter is determined based on the quantization matrix used for compression by the image compression unit 102 (step S112). The background removal parameter determination process is performed by the controller unit 202, and information on the used quantization matrix can be obtained from the image compression unit 102, the memory 103, or the image expansion unit 104. Further, the relationship between the quantization matrix and the background removal parameter is set in advance by a prior experiment or the like.

  Background removal is performed using the parameters determined in step S112 (step S113). Next, a compensation parameter is determined based on the quantization matrix used for the compression process (step S114). The compensation parameter determination process is performed by the controller unit 202, and information on the used quantization matrix can be obtained from the image compression unit 102, the memory 103, or the image expansion unit 104. Further, the relationship between the quantization matrix and the compensation parameter is previously set by a prior experiment or the like.

  Then, top cover compensation is performed using the parameters determined in step S114 (step S115). As schematically shown in FIG. 8 which shows a change in the luminance value of each pixel (pixel) in a certain image, the image before irreversible in FIG. 8 (a) and after the compensation processing in step S115 in FIG. 8 (e). It has the same brightness value as the image.

  As described above, it is possible to adaptively reduce mosquito noise by performing background removal and top surface compensation according to image degradation. It should be noted that the relationship between the ground and the ground can be exchanged, and noise reduction may be implemented by a combination of ground removal and ground supplement.

<Third Embodiment>
FIG. 12 is a block diagram showing a schematic configuration of an image forming apparatus according to the third embodiment of the present invention. In FIG. 12, an image forming apparatus 1210 receives a print job from a host computer 1250 and forms a visible image on a recording medium such as recording paper based on the print job. In the image forming apparatus 1210, the controller unit 1211 analyzes the print job received from the host computer 1250 and generates image data in a form that can be provided to the printer engine 1214.

  The CPU 1212 in the controller unit 1211 implements various controls by the image forming apparatus 1210 by executing a control program stored in the memory 1213. The printer engine 1214 forms a visible image on the recording paper according to the image data input from the controller unit 1211. Image processing in the controller unit 1211 will be described later with reference to FIG. Note that various printer engines such as an electrophotographic system, an inkjet system, and a thermal system can be applied to the printer engine 1214. Reference numeral 1205 denotes a hard disk for storing various data.

  In FIG. 12, a printer driver (not shown) corresponding to the image forming apparatus 1210 is installed in the host computer 1250 so as to be operable. For example, when a print instruction for a created document is issued from a certain application, a print job in a page description language (PDL) that can be analyzed by the image forming apparatus 1210 is generated by a printer driver and transmitted to the image forming apparatus 1210.

  FIG. 13 is a block diagram illustrating a configuration of an image processing unit of an image forming apparatus 1210 according to the third embodiment. Image processing performed by the controller unit 1211 of the image forming apparatus 1210 described with reference to FIG. 12 will be described with reference to FIG.

  The page description language rendering unit 1301 is a block that receives a print job from the host computer 1250 and performs PDL analysis and rendering. Specifically, the page description language rendering unit 1301 interprets the PDL command and generates a bitmap image having RGB values that are images for printing.

  The image compression unit 1302 is a block that compresses an image in order to store the image in the memory 1303, and compresses and encodes the image signal using an irreversible compression method (for example, the JPEG method in this embodiment). The compression process performs discrete cosine transform (DCT transform), which is a known spatial frequency transform in units of 8 × 8 pixels, quantizes the DCT coefficient using the set quantization matrix, and performs the Huffman coding process on the quantized value By doing. In compression, the RGB signal may be converted into a luminance color difference signal (YCbCr) and then compressed.

  In addition, since the main cause of image degradation is quantization error, the degree of image degradation is closely related to the quantization matrix used for quantization. Therefore, by using this relationship, parameters such as background removal processing in a printer image processing unit 1305 to be described later can be adaptively switched. In the present embodiment, the input to the image compression unit 1302 is an RGB signal, but it may be a CMYK signal.

  The image compressed by the image compression unit 1302 is temporarily stored in the memory 1303. The memory 1302 is a storage medium and may be a semiconductor storage element or a hard disk. The compressed data stored in the memory 1303 is decompressed by the image decompression unit 1304. The decompression process is performed by performing Huffman inverse coding on the compressed image signal, returning to a DCT coefficient value by a set inverse quantization matrix, and performing a discrete cosine inverse transform (DCT inverse transform) process. If the decompressed image signal is an RGB signal converted into a luminance color difference signal, it is converted into an RGB signal. In the present embodiment, the input to the image compression unit 1304 is an irreversibly compressed RGB signal, but it may be a CMYK signal.

  Details of processing in the printer image processing unit 1305 according to the second embodiment will be described with reference to FIG. First, the background removal unit 401 performs background removal processing based on parameters used in lossy compression. Background removal is an operation of pasting a portion having a luminance value close to the white level, called a background portion of an image, to the white level. In the case of an RGB signal, the white level is 255. For example, this is realized by converting the luminance value using a conversion table as shown in FIG. In the example shown in FIG. 5, the level of luminance value to be pasted to the white level is a parameter for the background removal process. The background removal method is arbitrary, and the conversion table is not limited to that shown in FIG. For example, it is possible to paste using a non-linear conversion table as shown in FIG.

  The background removal process is a process that can skip the mosquito noise portion of the image, but since it may have an adverse effect of destroying the highlight portion of the image, the selection of the background removal parameter is very important. Therefore, in the present embodiment, the selection of the background removal parameter is adaptively performed based on the parameter used in the lossy compression, thereby reducing the mosquito noise while minimizing the influence on the image.

  The parameters used in lossy compression include, for example, a quantization matrix used for compression. The main cause of image degradation due to lossy compression is a quantization error, and the quantization error has a strong correlation with a quantization matrix used for quantization. Therefore, experimentally, if the relationship between the quantization table to be used and the optimum parameter of the background removal process is obtained in advance and the background removal parameter is switched using the relationship, the background removal process according to the image degradation can be realized. . There is a conventional example using an image compression rate as an index for estimating image degradation, but the image compression rate is a value that depends on two main factors of image degradation and image complexity. It is not appropriate to estimate image degradation from The compression rate is not a parameter used for lossy compression, but an index obtained as a result of compression.

  The logarithmic conversion unit 402 and the color space conversion unit 403 convert RGB signals as luminance values into CMYK signals of cyan (C), magenta (M), yellow (Y), and black (K) as density values. This is because the toner used when printing with the printer is CMYK. The spatial filter unit 404 applies a known spatial filter that changes the frequency characteristics of the image. A gamma correction unit 405 performs gamma correction according to the characteristics of the printer unit. As a result, there is an effect of preventing the density of the printed matter after printing from changing even with the same digital gradation due to the characteristics of the printer unit. The halftoning unit 406 converts the CMYK signal into the number of gradations that can be expressed by the laser of the printer engine. The conversion processing at this time is processing that expresses a multi-value gradation in a pseudo manner. For example, an error diffusion process and a screen process are mentioned. The converted signal is output to the printer engine, and the subsequent processing is as described above.

  Processing for reducing lossy compression in the image forming apparatus of the present embodiment having the above-described configuration will be described with reference to the flowchart of FIG.

  The image decompression unit 1304 decompresses the image that has been subjected to the irreversible compression (step S71). Next, a background removal parameter is determined from the quantization matrix used for compression (step S72). This processing is performed by the controller 1211, but information on the used quantization matrix can be obtained from the image compression unit 1302, the memory 1303, or the image expansion unit 1304. It should be noted that the relationship between the quantization matrix and the background removal parameter is previously set by experiment or the like.

  Then, background removal is performed using the parameters determined in step S72 (step S73). Here, FIGS. 8A, 8 </ b> B, 8 </ b> C, and 8 </ b> D schematically show changes in the luminance value of each pixel (pixel) in an image with respect to the effect of the background removal according to the present embodiment. By performing the background processing adaptively based on the background removal parameter, a result as shown in FIG. 8C or FIG. 8D can be obtained.

  As described above, it is possible to adaptively reduce mosquito noise by performing background removal according to image degradation.

<Fourth Embodiment>
In the image forming apparatus according to the fourth embodiment, a compensation unit is added between the background processing unit 401 and the logarithmic conversion unit 402 of the printer image processing unit 1305 in the third embodiment described above. The printer image processing unit 1305 in this embodiment will be described with reference to FIG. The other parts such as the background removal unit 401, logarithmic conversion unit 402, color space conversion unit 403, spatial filter unit 404, gamma correction unit 405, and halftoning unit 406 are the same as those in the third embodiment described above. Therefore, the description is omitted.

  The compensation unit 901 is a part that compensates for an upper portion that has changed due to image degradation. Here, the upper ground is a portion having a luminance value close to the black level of the image. As shown in FIG. 8, image degradation does not occur only in the background portion, but naturally occurs in the upper portion. Therefore, in the present embodiment, image deterioration is corrected by compensating the upper portion.

  Two methods are conceivable as means for compensating for image degradation. The first method is a method of performing compensation by pasting the upper portion to the black level. In the case of an RGB signal, the black level is 0. For example, it is realized by converting the luminance value in units of pixels using a conversion table as shown in FIG. In this example, what level of luminance value is pasted to the black level is a parameter of the first compensation method. In this embodiment, the selection of the parameter is adaptively performed based on the parameter used in the lossy compression, thereby reducing the mosquito noise while minimizing the influence on the image. The parameters used in lossy compression include, for example, a quantization matrix used for compression. Further, in the first method, by removing the conversion tables shown in FIG. 5 and FIG. For this reason, when the first method is used, the base removal unit and the top cover filling unit can be combined into one processing unit.

  In the second method, processing is not performed on a pixel-by-pixel basis as in the first method described above, but the amount of compensation for the pixel of interest is determined from the background removal status of the surrounding pixels of the pixel of interest, and compensation is performed. is there. There is a strong correlation between the amount of change in the background portion of the image and the amount of change in the upper portion that occur due to lossy compression. In other words, the correlation is such that if the luminance value of the peripheral background portion decreases, the luminance value of the attention upper portion increases.

  In view of this correlation, if the top cover compensation amount is determined from the ground removal amount, there is a high possibility that an image before irreversible compression can be restored. Specifically, a process of calculating the total amount of background removal for each DCT conversion processing unit (8 × 8 pixel unit) and compensating for a certain ratio in the upper part is conceivable. In this case, the compensation ratio is a parameter. In the present embodiment, the selection of the parameter is adaptively performed based on the parameter used in the lossy compression, thereby reducing the mosquito noise while minimizing the influence on the image. The parameters used in lossy compression include, for example, a quantization matrix used for compression.

  Processing for reducing irreversible compression in the image forming apparatus of the present embodiment having the above-described configuration will be described with reference to the flowchart of FIG. First, the image decompression unit 1304 decompresses the image subjected to the irreversible compression by the image compression unit 1302 (step S111). Next, a background removal parameter is determined from the quantization matrix used for compression (step S112). This processing is performed by the controller unit 1211, and information on the used quantization matrix can be obtained from the image compression unit 1302, the memory 1303, or the image expansion unit 1304. It should be noted that the relationship between the quantization matrix and the background removal parameter is set in advance by experiments or the like.

  Next, background removal is performed using the parameters determined in step S112 (step S113). Then, a compensation parameter is determined from the quantization matrix used for compression (step S114). This processing is performed by the controller unit 1211, and information on the used quantization matrix can be obtained from the image compression unit 1302, the memory 1303, or the image expansion unit 1304. It should be noted that the relationship between the quantization matrix and the compensation parameter is set in advance by an experiment or the like.

  Further, the upper ground is compensated using the parameters determined in step S114 (step S115). In FIG. 8, (a), (c), (d), and (e) are diagrams showing the effects of this embodiment, and schematically show changes in the luminance value of each pixel (pixel) in a certain image. ing. The image before irreversible in FIG. 8A and the image after processing in step S115 in FIG. 8E have the same luminance value.

  As described above, mosquito noise can be adaptively reduced by performing background removal and compensation according to image degradation. In the above-described processing, the relationship between the ground and the ground can be further changed, and the processing can be performed by a combination of ground removal and ground supplement.

<Other embodiments>
The above-described embodiments are not limited to printing using copy or PDL, and can be applied to all image processing apparatuses using lossy compression.

  As described in each of the above embodiments, in the present invention, adaptive background removal based on the parameters at the time of irreversible compression, or adaptive background removal based on the parameters at the time of irreversible compression and the compensation of the upper ground. Thus, it is possible to suppress the generation of pseudo contours, suppress the shading of the shadow portion, and further reduce the deterioration of the image due to the irreversible compression.

  Although the embodiment has been described in detail above, the present invention can take an embodiment as, for example, a system, apparatus, method, program, or storage medium (recording medium). The present invention may be applied to a system composed of a single device or an apparatus composed of a single device.

  In the present invention, a software program (in the embodiment, a program corresponding to the flowchart shown in the figure) that realizes the functions of the above-described embodiment is directly or remotely supplied to the system or apparatus, and the computer of the system or apparatus Is also achieved by reading and executing the supplied program code.

  Accordingly, since the functions of the present invention are implemented by computer, the program code installed in the computer also implements the present invention. In other words, the present invention includes a computer program itself for realizing the functional processing of the present invention.

  In that case, as long as it has the function of a program, it may be in the form of object code, a program executed by an interpreter, script data supplied to the OS, or the like.

  As a recording medium for supplying the program, for example, floppy (registered trademark) disk, hard disk, optical disk, magneto-optical disk, MO, CD-ROM, CD-R, CD-RW, magnetic tape, nonvolatile memory card ROM, DVD (DVD-ROM, DVD-R) and the like.

  As another program supply method, a client computer browser is used to connect to an Internet homepage, and the computer program of the present invention itself or a compressed file including an automatic installation function is downloaded from the homepage to a recording medium such as a hard disk. Can also be supplied. It can also be realized by dividing the program code constituting the program of the present invention into a plurality of files and downloading each file from a different homepage. That is, a WWW server that allows a plurality of users to download a program file for realizing the functional processing of the present invention on a computer is also included in the present invention.

  In addition, the program of the present invention is encrypted, stored in a storage medium such as a CD-ROM, distributed to users, and key information for decryption is downloaded from a homepage via the Internet to users who have cleared predetermined conditions. It is also possible to execute the encrypted program by using the key information and install the program on a computer.

  In addition to the functions of the above-described embodiments being realized by the computer executing the read program, the OS running on the computer based on the instruction of the program is a part of the actual processing. Alternatively, the functions of the above-described embodiment can be realized by performing all of them and performing the processing.

  Furthermore, after the program read from the recording medium is written in a memory provided in a function expansion board inserted into the computer or a function expansion unit connected to the computer, the function expansion board or The CPU or the like provided in the function expansion unit performs part or all of the actual processing, and the functions of the above-described embodiments are realized by the processing.

FIG. 3 is a block diagram illustrating a detailed configuration of a controller unit 202 that performs image processing of the image forming apparatus 200 illustrated in FIG. 2. 1 is a schematic block diagram of an image forming apparatus 200 according to a first embodiment of the present invention. 1 is a cross-sectional view of a digital multi-function peripheral that realizes an image forming apparatus 200 according to a first embodiment. FIG. 3 is a block diagram illustrating a detailed configuration of a printer image processing unit 105 in a controller unit 202 that performs various types of image processing in the image forming apparatus 200 according to the first embodiment illustrated in FIG. 2. 6 is a diagram illustrating an example of a conversion table for background removal used in a background removal unit 401 of the printer image processing unit 105. FIG. FIG. 10 is a diagram illustrating another example of a conversion table for background removal used by the background removal unit 401 of the printer image processing unit 105. 5 is a flowchart for explaining noise reduction processing in the image forming apparatus according to the first embodiment of the present invention; 6 is a diagram for explaining an effect of noise reduction processing in the image forming apparatus 200. FIG. FIG. 10 is a block diagram illustrating a detailed configuration of a printer image processing unit 905 according to a second embodiment of the present invention. It is a figure which shows an example of the conversion table for the top surface compensation used by the compensation part 901 of the printer image process part 905 in 2nd Embodiment. 7 is a flowchart for explaining noise reduction processing in an image forming apparatus according to a second embodiment of the present invention; It is a block diagram which shows schematic structure of the image forming apparatus which concerns on the 3rd Embodiment of this invention. FIG. 10 is a block diagram illustrating a configuration of an image processing unit of an image forming apparatus 1210 according to a third embodiment.

Explanation of symbols

DESCRIPTION OF SYMBOLS 101 Scanner image processing part 102 Image compression part 103 Memory 104 Image expansion part 105 Printer image processing part 200 Image forming apparatus 201 Scanner part 202 Controller part 203 Printer part 204 Operation part 205 Memory 206 Network 207 Server 208 PC
401 ground removal unit 402 logarithmic conversion unit 403 color space conversion unit 404 spatial filter unit 405 gamma correction unit 406 half toning unit 901 compensation unit

Claims (13)

Compression means for irreversibly compressing image data;
Storage means for storing the image data compressed by the compression means;
Decompression means for decompressing the image data stored in the storage means;
Determining means for determining a parameter at the time of noise removal processing of the image data decompressed by the decompressing means, corresponding to a parameter used at the time of irreversible compression of the image data by the compressing means;
An image processing apparatus comprising: a noise removal unit that performs a noise removal process on the image data expanded by the expansion unit using the parameter determined by the determination unit.   The noise removal unit performs a background removal process for converting a substantially white level pixel of the image data expanded by the expansion unit into a white level pixel using the parameter determined by the determination unit. The image processing apparatus according to claim 1.   The image processing apparatus according to claim 1, further comprising a top compensation unit that converts a substantially black level pixel of the image data expanded by the expansion unit into a black level pixel using the parameter determined by the determination unit. 2. The image processing apparatus according to 2.   For each predetermined unit at the time of irreversible compression of the image data in the compression unit, the image data is compensated for a luminance value corresponding to a predetermined ratio of the total luminance value lost by the background removal processing by the noise removal unit. The image processing apparatus according to claim 2, further comprising upper land filling means.   5. The upper surface compensation means compensates the luminance value corresponding to a predetermined ratio of the total luminance value lost by the background removal processing to peripheral pixels of the pixel subjected to the background removal processing. An image processing apparatus according to 1.   A ratio determining means for determining a ratio of the luminance value to be compensated for peripheral pixels of the pixel subjected to the background removal processing by the background removing means based on a parameter used at the time of irreversible compression of the image data; The image processing apparatus according to claim 5, further comprising:   The noise removing unit performs a top removal process for converting a substantially black level pixel of the image data decompressed by the decompressing unit into a black level pixel using the parameter determined by the determining unit. The image processing apparatus according to claim 1, wherein:   8. The image processing apparatus according to claim 7, further comprising a background filling unit that converts a substantially white level pixel of the image data expanded by the expansion unit into a white level pixel using the parameter determined by the determination unit. An image processing apparatus according to 1.   For each predetermined unit at the time of irreversible compression of the image data in the compression unit, the image data is compensated for a luminance value corresponding to a predetermined ratio of the total luminance value lost by the background removal processing by the noise removal unit. The image processing apparatus according to claim 7, further comprising a background filling means for performing the processing.   The image processing apparatus according to claim 1, wherein the parameter is a quantization matrix used during the lossy compression. A compression process for irreversibly compressing image data;
A storage step of storing the image data compressed in the compression step in a storage means;
A decompression step of decompressing the image data stored in the storage means;
A determination step for determining a parameter at the time of noise removal processing of the image data decompressed by the decompression step in response to a parameter used at the time of irreversible compression of the image data by the compression step;
A noise removal step of performing a noise removal process on the image data decompressed in the decompression step using the parameters determined in the determination step. On the computer,
A compression procedure for irreversibly compressing image data;
A storage procedure for storing the image data compressed in the compression procedure in a storage means;
A decompression procedure for decompressing the image data stored in the storage means;
A determination procedure for determining a parameter at the time of noise removal processing of the image data decompressed by the decompression procedure in response to a parameter used at the time of irreversible compression of the image data by the compression procedure;
And a noise removal procedure for performing a noise removal process on the image data decompressed by the decompression procedure using the parameters determined by the determination procedure.   A computer-readable storage medium storing the program according to claim 12.

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