Image processing method and image processing apparatus

Abstract

To obtain compressed image data with a good balance between image quality and a compression ratio and not exceeding an allowable size.SOLUTION: A data processing apparatus 51 divides an image area into a first area and a second area including an edge image. The data processing apparatus 51 counts the number of first edges in each of a plurality of first data blocks corresponding to the first area, and the number of second edges in each of a plurality of second data blocks corresponding to the second area. The data processing apparatus 51 derives an estimated value of the data size of each of a plurality of pieces of first post-compression data on the basis of the number of first edges and a first compression parameter, and derives an estimated value of the data size of each of a plurality of pieces of second post-compression data on the basis of the number of second edges and a second compression parameter. The data processing apparatus 51 generates the plurality of pieces of first post-compression data and the plurality of pieces of second post-compression data by using the first compression parameter and the second compression parameter when the total of the estimated values falls within an allowable size.SELECTED DRAWING: Figure 2

Description

[Technical Field]

[0001] The present invention relates to an image processing method and an image processing device for compressing image data. [Background technology]

[0002] Image processing devices such as copying machines, facsimile machines, and multifunction peripherals have a function for compressing image data.

[0003] When image data is compressed using a lossless compression method, high-quality compressed image data is obtained, but the compression ratio is relatively low. On the other hand, when image data is compressed using a lossy compression method, the compression ratio is high, but noise may occur in some parts of the image based on the compressed image data.

[0004] It is also known that an image compression device divides image data into a plurality of blocks, compresses each of the blocks using a lossless compression means and a lossy compression means to generate two compressed block data, and selects one of the two compressed block data for each block (see, for example, Patent Document 1). For example, the image compression device selects data according to the cumulative amount of information generated by the lossless compression and the number of colors for each block. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] Japanese Patent Application Publication No. 8-167030 Summary of the Invention [Problem to be solved by the invention]

[0006] Meanwhile, there is a need to obtain compressed image data that has a good balance between image quality and compression ratio by performing image processing on original image data as simply as possible.

[0007] Furthermore, there is a need to compress the original image data so that the size of the compressed image data does not exceed a preset allowable size.

[0008] An object of the present invention is to provide an image processing method and an image processing device that can obtain compressed image data that has a good balance between image quality and compression ratio and does not exceed the allowable size by performing image processing on original image data as simply as possible. [Means for solving the problem]

[0009] An image processing method according to one aspect of the present invention includes a data processing device detecting an edge image consisting of a plurality of consecutive edge pixels by performing an edge detection process on input image data. The image processing method further includes the data processing device dividing an image region of the input image data into a first region, which is a rectangular region surrounding the edge image, and a second region other than the first region. The image processing method further includes the data processing device counting a first edge number, which is the number of edge pixels for each of a plurality of first data blocks corresponding to the first region among a plurality of data blocks constituting the input image data. The image processing method further includes the data processing device counting a second edge number, which is the number of edge pixels for each of a plurality of second data blocks corresponding to the second region among the plurality of data blocks constituting the input image data. The image processing method further includes the data processing device performing a first size estimation process to derive an estimated value of the data size of each of the plurality of first compressed data blocks obtained when each of the plurality of first data blocks is compressed by a lossy compression method using the first compression parameter by applying the first edge number and the first compression parameter to a size estimation rule that represents a correspondence relationship between the number of edge pixels included in pre-compression data, the compression parameter, and the size of the compressed data.The image processing method further includes the data processing device performing a second size estimation process to derive an estimated value of the data size of each of the plurality of second compressed data blocks obtained when each of the plurality of second data blocks is compressed by the lossy compression method using the second compression parameter by applying the second edge number and a second compression parameter that has a higher compression ratio than the first compression parameter to the size estimation rule.The image processing method further includes the data processing device performing an adopted parameter setting process to set a combination of the first compression parameter and the second compression parameter when the sum of the first size estimation process and the plurality of size estimates corresponding to the plurality of data blocks obtained by the first size estimation process falls within a predetermined allowable size.The image processing method further includes the data processing device compressing each of the plurality of first data blocks and each of the plurality of second data blocks by the lossy compression method using the first compression parameter and the second compression parameter set by the adopted parameter setting process to generate a plurality of first compressed data corresponding to the plurality of first data blocks and a plurality of second compressed data corresponding to the plurality of second data blocks.The image processing method further includes the data processing device generating output image data that is compressed data of the input image data by combining the plurality of first compressed data and the plurality of second compressed data.

[0010] An image processing device according to another aspect of the present invention includes an image data acquisition device that acquires image data, and a data processing device that realizes the image processing method, in which data obtained by the image data acquisition device is processed as input image data. [Effects of the Invention]

[0011] According to the present invention, it is possible to provide an image processing method and an image processing device that can obtain compressed image data that has a good balance between image quality and compression ratio and does not exceed the allowable size by performing as simple image processing as possible on original image data. [Brief explanation of the drawings]

[0012] [Figure 1] FIG. 1 is a block diagram showing the configuration of an image processing apparatus according to the first embodiment. [Figure 2] FIG. 2 is a block diagram showing the configuration of a plurality of processing modules included in the image processing unit in the image processing apparatus according to the first embodiment. [Figure 3] FIG. 3 is a block diagram showing the configuration of an image processing apparatus according to the second embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0013] Hereinafter, an embodiment of the present invention will be described with reference to the drawings. Note that the following embodiment is an example of the present invention, and does not limit the technical scope of the present invention.

[0014] [First embodiment] The image processing device 10 according to the first embodiment is capable of executing various types of image processing such as image formation processing, image reading processing, image transmission processing, etc. For example, the image processing device 10 is a copying machine, a facsimile machine, a multifunction peripheral, or the like.

[0015] In the example shown in FIG. 1, an image processing apparatus 10 includes a printing device 1, an image reading device 2, a user interface device 3, a communication device 4, a control device 5, and a secondary storage device 6.

[0016] The image processing device 10 is capable of communicating with other devices such as a host device 8 through a network 80. The network 80 includes a LAN (Local Area Network) and the Internet.

[0017] The printing apparatus 1 executes the image forming process by a predetermined method such as an electrophotographic method or an inkjet method. The image forming process is a process of forming an image on a sheet 91.

[0018] The printing apparatus 1 includes a sheet transport mechanism that transports a sheet 91 and a printing device that forms an image on the sheet 91 .

[0019] The image reading device 2 executes the image reading process. The image reading process is a process of reading an image from an original 92 and outputting data of the read image. The image reading device 2 includes an optical scanning mechanism that scans light onto the original 92, and an image sensor that receives light reflected from the original 92.

[0020] The image sensor outputs data of the read image, which is an image read from the document 92.

[0021] The image processing device 10 also includes a frame memory 20 capable of storing image data. The image reading device 2 stores the read image data in the frame memory 20.

[0022] The user interface device 3 includes an operation device 3a and a display device 3b. The operation device 3a is a device that accepts human operations. For example, the operation device 3a includes operation buttons and a touch panel. The display device 3b is capable of displaying information. For example, the display device 3b includes a display panel such as a liquid crystal panel.

[0023] The communication device 4 is a communication interface device that communicates with other devices such as a host device 8 via a network 80. The control device 5 performs all data transmission and reception with the other devices through the communication device 4.

[0024] The printing device 1 executes the image forming process based on the scanned image data or the received print data, which is data included in a print request received from the host device 8 via the communication device 4.

[0025] The communication device 4 is also capable of executing the image transmission process, which is a process of transmitting the data of the scanned image to a specified destination via the network 80.

[0026] The control device 5 executes various calculations, data processing, and control of various electrical devices included in the image processing device 10. The control device 5 includes a CPU 51, a RAM (Random Access Memory) 52, and the like.

[0027] The secondary storage device 6 is a computer-readable non-volatile storage device. The secondary storage device 6 can store computer programs and various data. For example, one or both of an SSD (Solid State Drive) and a hard disk drive may be used as the secondary storage device 6.

[0028] The secondary storage device 6 stores the computer programs executed by the CPU 51 and data referenced by the CPU 51. The CPU 51 is an example of a processor.

[0029] The CPU 51 is a processor that executes the computer programs stored in the secondary storage device 6 to perform various data processing and control operations.

[0030] It is also conceivable that another processor such as a DSP may perform the data processing and control instead of the CPU 51.

[0031] The RAM 52 is a computer-readable volatile storage device that temporarily stores the computer programs executed by the CPU 51 and data output and referenced during the execution of the computer programs by the CPU 51.

[0032] The CPU 51 includes a plurality of processing modules that are realized by executing the computer programs, including a job control unit 5a and an image processing unit 5b.

[0033] The job control unit 5a controls the printing device 1, the image reading device 2, and the communication device 4. The job control unit 5a causes some or all of the printing device 1, the image reading device 2, and the communication device 4 to execute a job corresponding to a request input through the operation device 3a or the communication device 4.

[0034] The job includes some or all of the multiple types of image processing, and in this embodiment, the job includes an image scanning job, a print job, and a copy job.

[0035] The image reading job includes the image reading process executed by the operation of the image reading device 2. The print job includes the image forming process executed by the operation of the printing device 1. The copy job includes the image reading process and the image forming process executed by the operations of the image reading device 2 and the printing device 1. In other words, the job includes one or more types of image processing.

[0036] The image processing unit 5b executes various types of image processing on the image data stored in the frame memory 20. In this embodiment, the image processing unit 5b executes image data compression processing to compress the image data stored in the frame memory 20.

[0037] For example, the image reading job includes the image reading process and the image data compression process executed by the image processing unit 5b. In this case, the image processing unit 5b compresses the data of the read image stored in the frame memory 20 and outputs the compressed data of the read image.

[0038] Furthermore, the image reading job includes an image data saving process for saving the compressed data of the read image in a secondary storage device 6, or an image transmission process for transmitting the compressed data of the read image to another device such as a host device 8 via a communication device 4.

[0039] When image data is compressed using a lossless compression method, high-quality compressed image data is obtained, but the compression ratio is relatively low. On the other hand, when image data is compressed using a lossy compression method, the compression ratio is high, but noise may occur in some parts of the image based on the compressed image data.

[0040] Meanwhile, there is a need to obtain compressed image data that has a good balance between image quality and compression ratio by performing image processing on original image data as simply as possible.

[0041] Furthermore, there is a need to compress the original image data so that the size of the compressed image data does not exceed a preset allowable size.

[0042] In this embodiment, the image processing unit 5b performs image data compression processing on the original image data using the simplest possible image processing to obtain compressed image data that has a good balance between image quality and compression ratio and does not exceed the allowable size.

[0043] [Image data compression processing] The image data compression process executed by the image processing unit 5b will be described below with reference to Fig. 2. Fig. 2 shows the configuration of a plurality of processing modules included in the image processing unit 5b.

[0044] For example, the input image data D1 to be subjected to the image data compression process is data of the scanned image obtained by the image reading device 2. The input image data D1 may also be image data obtained by the communication device 4 from the host device 8.

[0045] The image reading device 2 and the communication device 4 are each an example of an image data acquisition device that acquires input image data D1.

[0046] The image data compression process is an example of a process that realizes an image processing method. The CPU 51 including the image processing unit 5b is an example of a data processing device that realizes the image processing method. The image processing unit 5b includes the plurality of processing modules.

[0047] The multiple processing modules in the image processing unit 5b include an edge image detection unit 501, an area division unit 502, a block discrimination unit 503, an edge counting unit 504, a parameter set selection unit 505, a size estimation unit 506, a total size determination unit 507, a parameter set setting unit 508, a block selection unit 509, a data compression unit 510, and a synthesis processing unit 511.

[0048] The edge image detection unit 501 performs edge detection processing on the input image data D1 to detect an edge image made up of a plurality of continuous edge pixels.

[0049] For example, the edge detection process includes a differential value derivation process and an edge data derivation process. The differential value derivation process is a process of deriving differential values ​​in the X-axis direction and the Y-axis direction for a plurality of pixels in the input image data D1. The edge data derivation process is a process of deriving data consisting of the logical sum of binary data of the differential value in the X-axis direction and binary data of the differential value in the Y-axis direction for each of a plurality of pixels as edge data D11. The edge data D11 is data representing the edge image.

[0050] The region partitioning unit 502 partitions a rectangular region surrounding the edge image in the edge data D11 as a first region, and outputs first region coordinate data D12 representing the coordinates of the first region. The process of deriving the rectangular region surrounding the edge image is so-called bounding box processing.

[0051] The area other than the first area corresponding to the first area coordinate data D12 in the image area of ​​the input image data D1 is the second area.

[0052] The processing of the region dividing unit 502 is an example of region dividing processing for dividing the image region of the input image data D1 into the first region and the second region other than the first region.

[0053] The block discrimination unit 503 discriminates whether each of the plurality of data blocks constituting the input image data D1 corresponds to the first region or the second region, based on the first region coordinate data D12. The plurality of data blocks are data obtained by dividing the input image data D1 into predetermined unit regions. For example, each of the plurality of data blocks is data for 64 pixels, consisting of 8 pixels in the X-axis direction and 8 pixels in the Y-axis direction.

[0054] For example, the block determining unit 503 determines that a plurality of data blocks in which more than a predetermined number of pixels belong to the first region are a plurality of first data blocks corresponding to the first region.

[0055] On the other hand, the block discrimination unit 503 discriminates a plurality of data blocks in which the pixels exceeding the predetermined number do not belong to the first region as a plurality of second data blocks corresponding to the second region.

[0056] The block discrimination unit 503 outputs block type data D13 indicating whether each of the plurality of data blocks is the first data block or the second data block.

[0057] The edge count unit 504 executes edge counting processing to count the first edge number and the second edge number based on the edge data D11 and the block type data D13. The first edge number is the number of edge pixels for each of the first data blocks corresponding to the first region among the plurality of data blocks constituting the input image data D1. The second edge number is the number of edge pixels for each of the second data blocks corresponding to the second region among the plurality of data blocks constituting the input image data D1.

[0058] When the edge counting unit 504 finishes counting the first edge number and the second edge number, it outputs edge number data EN1 representing the first edge number for each first data block and the second edge number for each second data block, and an end notification indicating the end of counting.

[0059] The parameter set selection unit 505 starts processing in response to the output of the end notification by the edge counting unit 504. The parameter set selection unit 505 selects one target parameter set P1, P2 from a plurality of candidate parameter sets, each of which is a candidate combination of the first compression parameters and the second compression parameters.

[0060] The target parameter sets P1 and P2 include a first target parameter P1, which is one of the candidates for the first compression parameter, and a second target parameter P2, which is one of the candidates for the second compression parameter.

[0061] The first compression parameter and the second compression parameter are parameters used in the data compression process using a lossy compression method executed by a data compression unit 510, which will be described later.

[0062] The first compression parameter and the second compression parameter are parameters that affect the data compression rate, and the second compression parameter is a parameter that provides a higher compression rate than the first compression parameter.

[0063] That is, the second target parameter P2 is a parameter with a higher compression rate than the first target parameter P1.

[0064] In this embodiment, the data compression unit 510 performs the data compression process in the JPEG format. The first compression parameter and the second compression parameter are QUALITY parameters in the JPEG format. In this case, the multiple candidate parameter sets are multiple QUALITY parameter sets.

[0065] For example, the multiple QUALITY parameter sets include multiple combinations such as (90,50), (80,45) and (70,40).

[0066] The size estimation unit 506 executes a first size estimation process and a second size estimation process based on the edge count data EN1 and the target parameter sets P1 and P2.

[0067] In the following description, the plurality of data obtained when each of the plurality of first data blocks is compressed by the lossy compression method using the first compression parameters will be referred to as a plurality of first compressed data.

[0068] Similarly, a plurality of pieces of data obtained when each of the plurality of second data blocks is compressed by the lossy compression method using the second compression parameters are referred to as a plurality of second compressed data.

[0069] The first size estimation process is a process for deriving an estimate of the data size of each of the plurality of first compressed data blocks obtained when each of the plurality of first data blocks is compressed by the lossy compression method using a first target parameter P1. In the following description, the estimates corresponding to each of the plurality of first compressed data blocks are referred to as a plurality of first estimated values ​​EV1.

[0070] The second size estimation process is a process for deriving an estimate of the data size of each of the plurality of second compressed data blocks obtained when each of the plurality of second data blocks is compressed by the lossy compression method using a second target parameter P2. In the following description, the estimates corresponding to each of the plurality of second compressed data blocks are referred to as a plurality of second estimated values ​​EV2.

[0071] The size estimation unit 506 executes the first size estimation process and the second size estimation process using a predetermined size estimation rule, which represents the correspondence relationship between the number of edge pixels included in the uncompressed data, the compression parameters, and the size of the compressed data.

[0072] For example, the size estimation rule may be a formula or a look-up table that derives the size of the compressed data based on the number of edge pixels and the value of the compression parameter.

[0073] The number of edge pixels detected in the pre-compression data is highly correlated with the size of the compressed data, and the size estimation rule is set based on the results of a data compression test in which multiple test image data sets, each of which has a different number of detected edge pixels, are compressed.

[0074] In the first size estimation process, the size estimation unit 506 derives a plurality of first estimated values ​​EV1 by applying the first number of edges in the edge number data EN1 and the first object parameter P1 to the size estimation rule.

[0075] In the second size estimation process, the size estimation unit 506 derives a plurality of second estimated values ​​EV2 by applying the second number of edges in the edge number data EN1 and the second object parameter P2 to the size estimation rule.

[0076] A plurality of first estimated values ​​EV1 and a plurality of second estimated values ​​EV2 are the first size estimation process and a plurality of size estimates corresponding to the plurality of data blocks obtained by the first size estimation process.

[0077] The total size determination unit 507 determines whether the total size, which is the sum of the plurality of first estimated values ​​EV1 and the plurality of second estimated values ​​EV2, falls within a preset allowable size or not.

[0078] The total size determination unit 507 outputs an NG notification when the total size does not fall within the allowable size, and outputs an OK notification when the total size falls within the allowable size.

[0079] The parameter set selection unit 505 selects target parameter sets P1 and P2 in response to the output of the end notification by the edge counting unit 504, and then sequentially selects new target parameter sets P1 and P2 each time the total size determination unit 507 outputs the NG notification.

[0080] For example, the parameter set selection unit 505 selects target parameter sets P1 and P2 from among the plurality of candidate parameter sets, giving priority to those including parameters with low data compression rates.

[0081] Each time the parameter set selection unit 505 selects the target parameter sets P1 and P2, the size estimation unit 506 sequentially executes the first size estimation process and the second size estimation process using the selected target parameter sets P1 and P2.

[0082] The total size determination unit 507 derives the total size and determines whether the total size falls within the allowable size each time the first size estimation process and the second size estimation process are executed.

[0083] The parameter set setting unit 508 sets the target parameter sets P1 and P2 as adopted parameter sets PA1 and PA2 when the OK notification is output from the total size determination unit 507. The adopted parameter sets PA1 and PA2 are sets of compression parameters used in the data compression process.

[0084] The processing of the parameter set selection unit 505, the size estimation unit 506, the total size determination unit 507, and the parameter set setting unit 508 is an example of an adopted parameter setting process that sets a combination of the first compression parameter and the second compression parameter when the total size falls within the allowable size.

[0085] The adopted parameter sets PA1 and PA2 include the first adopted parameter PA1 and the second adopted parameter PA2, which are the first target parameter P1 and the second target parameter P2 when the OK notification is output.

[0086] The block selection unit 509 starts operation in response to the output of the OK notification from the total size determination unit 507 .

[0087] The block selection unit 509 selects each of the plurality of data blocks constituting the input image data D1 as a target block BD1. The target block BD1 is data to be subjected to data compression processing.

[0088] For example, the block selection unit 509 sequentially selects data for 64 pixels, consisting of 8 pixels in the X-axis direction and 8 pixels in the Y-axis direction, as the current block BD1.

[0089] The data compression section 510 selects one of the first adopted parameter PA1 and the second adopted parameter PA2 as the reference parameter to be used for compressing the target block BD1, based on the block type data D13.

[0090] Specifically, the data compression section 510 determines whether the target block BD1 is the first data block or the second data block based on the block type data D13.

[0091] When the target block BD1 is the first data block, the data compression unit 510 selects the first adopted parameter PA1 as the reference parameter, whereas when the target block BD1 is the second data block, the data compression unit 510 selects the second adopted parameter PA2 as the reference parameter.

[0092] Furthermore, the data compression unit 510 compresses the current block BD1 in JPEG format using the reference parameters.

[0093] The data compression unit 510 sequentially selects the reference parameters corresponding to the target blocks BD1 sequentially selected by the block selection unit 509, and compresses the sequentially selected target blocks BD1 using the corresponding reference parameters.

[0094] The data compression unit 510 sequentially generates and outputs compressed data blocks BD2 by performing JPEG compression processing on sequentially selected target blocks BD1.

[0095] That is, the data compression unit 510 compresses each of the first data blocks among the plurality of data blocks constituting the input image data D1 using the first adopted parameter PA1 in the JPEG format. As a result, the data compression unit 510 generates a plurality of first compressed data. Each of the first compressed data is a compressed data block BD2 compressed using the first adopted parameter PA1.

[0096] Furthermore, the data compression unit 510 compresses each of the second data blocks among the plurality of data blocks constituting the input image data D1 using the second adopted parameter PA2 in the JPEG format. As a result, the data compression unit 510 generates a plurality of second compressed data. Each of the second compressed data is a compressed data block BD2 compressed using the second adopted parameter PA2.

[0097] When data compression processing using a lossy compression method such as the JPEG method is performed with parameters for a high compression rate, noise is likely to occur in the first region, which has many edge portions.

[0098] When the target block BD1 is the first data block overlapping the first region, the first adopted parameter PA1 with a relatively low compression rate is used for data compression, thereby obtaining a compressed data block BD2 with less noise.

[0099] The synthesis processing unit 511 synthesizes the plurality of first compressed data and the plurality of second compressed data to generate output image data D2, which is compressed data of the input image data D1.

[0100] By employing the image data compression process, it is possible to obtain output image data D2 with a good balance between image quality and compression ratio by performing relatively simple image processing on the input image data D1.

[0101] Furthermore, the combination of the first adopted parameters PA1 and the second adopted parameters PA2 is set so that the sum of the multiple first estimated values ​​EV1 and the multiple second estimated values ​​EV2 falls within the allowable size, thereby obtaining output image data D2 that does not exceed the allowable size in most cases.

[0102] [Second embodiment] Next, an image processing device 10A according to a second embodiment will be described with reference to Fig. 3. In Fig. 3, the same components as those shown in Fig. 1 are denoted by the same reference numerals.

[0103] The image processing device 10A has a configuration in which a compression circuit 7 is added to the image processing device 10. The compression circuit 7 is a circuit that realizes, by hardware, the edge image detection unit 501, area division unit 502, block discrimination unit 503, edge count unit 504, parameter set selection unit 505, size estimation unit 506, total size determination unit 507, parameter set setting unit 508, block selection unit 509, data compression unit 510, and synthesis processing unit 511 shown in FIG.

[0104] That is, the compression circuit 7 includes an edge image detection circuit that realizes the edge image detection unit 501, an area division circuit that realizes the area division unit 502, a block discrimination circuit that realizes the block discrimination unit 503, an edge count circuit that realizes the edge count unit 504, a parameter set selection circuit that realizes the parameter set selection unit 505, a size estimation circuit that realizes the size estimation unit 506, a total size judgment circuit that realizes the total size judgment unit 507, a parameter set setting circuit that realizes the parameter set setting unit 508, a block selection circuit that realizes the block selection unit 509, a data compression circuit that realizes the data compression unit 510, and a synthesis processing circuit that realizes the synthesis processing unit 511.

[0105] The compression circuit 7 is an example of a data processing device that realizes the image processing method. When the image processing device 10A is used, the same effects as when the image processing device 10 is used can be obtained.

[0106] [Notes on the Invention] The following is a summary of the invention extracted from the above-described embodiment. Note that the configurations and processing functions described in the following supplementary notes can be selected and combined as desired.

[0107] <Appendix 1> a data processing device performing edge detection processing on input image data to detect an edge image made up of a plurality of continuous edge pixels; the data processing device divides an image area of ​​the input image data into a first area which is a rectangular area surrounding the edge image and a second area other than the first area; the data processing device counts a first edge number, which is the number of edge pixels for each of a plurality of first data blocks corresponding to the first region among a plurality of data blocks constituting the input image data; the data processing device counts a second edge number, which is the number of edge pixels for each of a plurality of second data blocks corresponding to the second region among the plurality of data blocks constituting the input image data; the data processing device executes a first size estimation process to derive an estimate of the data size of each of the plurality of first compressed data blocks obtained when each of the plurality of first data blocks is compressed by a lossy compression method using the first compression parameter by applying the first edge number and the first compression parameter to a size estimation rule that represents a correspondence relationship between the number of edge pixels included in pre-compression data, the compression parameter, and the size of compressed data; the data processing device executes a second size estimation process that derives an estimate of the data size of each of a plurality of second compressed data blocks obtained when each of the plurality of second data blocks is compressed by the lossy compression method using the second compression parameter by applying the second edge number and a second compression parameter that is a parameter having a higher compression rate than the first compression parameter to the size estimation rule; the data processing device executes the first size estimation process and an adopted parameter setting process that sets a combination of the first compression parameter and the second compression parameter when a sum of a plurality of size estimate values ​​corresponding to the plurality of data blocks obtained by the first size estimation process falls within a predetermined allowable size; the data processing device compresses each of the plurality of first data blocks and each of the plurality of second data blocks by the lossy compression method using the first compression parameter and the second compression parameter set by the adopted parameter setting process, thereby generating a plurality of first compressed data corresponding to the plurality of first data blocks and a plurality of second compressed data corresponding to the plurality of second data blocks; The image processing method includes the data processing device generating output image data that is compressed data of the input image data by combining the plurality of first compressed data and the plurality of second compressed data.

[0108] <Appendix 2> The adopted parameter setting process includes: the data processing device sequentially selecting a target parameter set from a plurality of candidate parameter sets, each of which is a candidate for a combination of the first compression parameters and the second compression parameters; the data processing device sequentially performs the first size estimation process and the second size estimation process using the target parameter set; The image processing method described in Appendix 1 includes the step of: setting, by the data processing device, the target parameter set when the sum of the multiple size estimation values ​​corresponding to the multiple data blocks obtained by the first size estimation process and the second size estimation process falls within the allowable size as the first compression parameters and the second compression parameters used to compress the input image data.

[0109] <Appendix 3> the lossy compression method is the JPEG method, The image processing method according to claim 1 or 2, wherein the first compression parameter and the second compression parameter are QUALITY parameters in the JPEG format.

[0110] <Appendix 4> an image data acquisition device that acquires image data; and a data processing device that implements the image processing method according to any one of Supplementary Note 1 to Supplementary Note 3, which processes data obtained by the image data acquisition device as input image data.

[0111] <Appendix 5> 5. The image processing device according to claim 4, wherein the image data acquisition device is an image reading device that reads an image from a document. [Explanation of symbols]

[0112] 1: Printing device 2: Image reader 3: User interface device 4: Communication equipment 5: Control device 6 :Secondary storage device 7: Compression circuit (data processing device) 10: Image processing device 10A: Image processing device 20: Frame memory 51: CPU (Data Processing Unit)

Claims

1. a data processing device performing edge detection processing on input image data to detect an edge image made up of a plurality of continuous edge pixels; the data processing device divides an image area of ​​the input image data into a first area which is a rectangular area surrounding the edge image and a second area other than the first area; the data processing device counts a first edge number, which is the number of edge pixels for each of a plurality of first data blocks corresponding to the first region among a plurality of data blocks constituting the input image data; the data processing device counts a second edge number, which is the number of edge pixels for each of a plurality of second data blocks corresponding to the second region among the plurality of data blocks constituting the input image data; the data processing device executes a first size estimation process to derive an estimate of the data size of each of the plurality of first compressed data blocks obtained when each of the plurality of first data blocks is compressed by a lossy compression method using the first compression parameter by applying the first edge count and the first compression parameter to a size estimation rule that represents a correspondence relationship between the number of edge pixels included in pre-compression data, the compression parameter, and the size of compressed data; the data processing device executes a second size estimation process that derives an estimate of a data size of each of a plurality of second compressed data blocks obtained when each of the plurality of second data blocks is compressed by the lossy compression method using the second compression parameter by applying the second edge number and a second compression parameter that is a parameter having a higher compression rate than the first compression parameter to the size estimation rule; the data processing device executes the first size estimation process and an adopted parameter setting process for setting a combination of the first compression parameter and the second compression parameter when a sum of a plurality of size estimate values ​​corresponding to the plurality of data blocks obtained by the first size estimation process falls within a predetermined allowable size; the data processing device compresses each of the plurality of first data blocks and each of the plurality of second data blocks by the lossy compression method using the first compression parameter and the second compression parameter set by the adopted parameter setting process, thereby generating a plurality of first compressed data corresponding to the plurality of first data blocks and a plurality of second compressed data corresponding to the plurality of second data blocks; the data processing device generating output image data that is compressed data of the input image data by combining the plurality of first compressed data and the plurality of second compressed data.

2. The adopted parameter setting process includes: the data processing device sequentially selecting a target parameter set from a plurality of candidate parameter sets, each of which is a candidate for a combination of the first compression parameters and the second compression parameters; the data processing device sequentially performs the first size estimation process and the second size estimation process using the target parameter set; 2. The image processing method of claim 1, further comprising: setting the target parameter set when the sum of the plurality of size estimation values ​​corresponding to the plurality of data blocks obtained by the first size estimation process and the second size estimation process falls within the allowable size as the first compression parameters and the second compression parameters to be used for compressing the input image data.

3. the lossy compression method is the JPEG method, 3. The image processing method according to claim 1, wherein the first compression parameter and the second compression parameter are quality parameters in the JPEG format.

4. an image data acquisition device that acquires image data; 3. An image processing apparatus comprising: a data processing apparatus that implements the image processing method according to claim 1 or 2, and processes data obtained by the image data acquisition apparatus as input image data.

5. The image processing apparatus according to claim 4 , wherein the image data acquisition device is an image reading device that reads an image from a document.

Images