JP2005295307A - Image compression method,image compression device, image expanding device, and program - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a technology which is possible to realize a better compression ratio in a reversible compression processing of a two-valued image. <P>SOLUTION: In the two-valued image compressing method, concretely, the two-valued image is divided into a unit pixel block B of a predetermined size (for example, 4×2 pixel). Further, each unit pixel block B has a pixel string composed of a plurality of pixels in a sub-scanning direction. And, rearrangement of pixel values in the two-valued image is performed by repeating operations to read out pixel values of a plurality of pixels in the unit pixel block B in a predetermined order for the plurality of unit pixel blocks arranged in the main scanning direction in the two-valued image, and the compression is made applied to the predetermined reversible compression method for arrangement of pixel values after rearrangement. Moreover, at the time of expanding (defrosting), expanding processing and rearrangement processing are performed in the reverse procedure. <P>COPYRIGHT: (C)2006,JPO&NCIPI

Description

  The present invention relates to a binary image compression technique and decompression technique.

  As image compression processing methods, there are a reversible method (lossless) and an irreversible method (lossy).

  The reversible method is a method that can completely obtain the same information as the original information when decompressing the compressed information. As the reversible method, a run length method, a universal coding method (LZSS method, LZW method), a partial match prediction method, a block sorting method, and the like are known.

  On the other hand, the irreversible method is a method that cannot completely obtain the same information as the original information when decompressing the compressed information. In the irreversible method, a good compression rate is realized by reducing information that has less visual effect using visual characteristics. As this irreversible method, JPEG using DCT (discrete cosine transform) or the like, JPEG2000 using wavelet transform or the like are known.

  Both of these methods are appropriately selected and used according to the properties of the file to be compressed. For example, in image compression processing, an irreversible method that is advantageous in terms of compression rate is often used. However, when it is required to obtain information that completely matches information before compression (original information) as decompression information after decompression processing, the lossless method is also used in image compression processing.

  By the way, the “reversible method” has an advantage that the same information as the original information can be obtained at the time of restoration, but the degree of compression is generally smaller than that of the irreversible method.

  Therefore, there are reversible compression techniques that have been devised in various ways to achieve a better compression ratio while obtaining the advantage that the same information as the original information can be obtained at the time of restoration.

  For example, when the target image is a multi-valued image, there is a technique for further increasing the degree of compression using a characteristic unique to the multi-valued image (see, for example, Patent Document 1). A multi-valued image has a property that the correlation between adjacent pixels is high, and in particular, the higher the bit position of each pixel value, the higher the probability that the bit values are the same between adjacent pixels. In this technique, by using such a property, as a pre-process for performing the image compression process, the bit rate of the multi-valued image data is rearranged so that the same bit positions of adjacent pixels are continuous, thereby compressing the compression rate. Has been made to improve.

JP 2001-309185 A

  By the way, the image includes not only a “multi-valued image” in which the gradation value (pixel value) of each pixel is expressed in three or more levels (for example, 256 levels) but also the gradation value of each pixel in two levels. There is also a “binary image” expressed by (for example, “0” and “1”).

  There is also a demand for compressing such a binary image by a reversible method rather than an irreversible method.

  However, the above-described technique is based on the premise that the target image is a multi-valued image, and uses the properties of the multi-valued image to improve the compression ratio. Therefore, when performing reversible compression of a binary image. It cannot be applied as it is.

  Therefore, an object of the present invention is to provide a technique capable of realizing a better compression rate in the reversible compression processing of a binary image.

  In order to solve the above-mentioned problem, the invention of claim 1 is directed to a computer for performing (a) an operation of reading pixel values of a plurality of pixels in each unit pixel block in a binary image in a predetermined order in the binary image. A procedure for rearranging pixel values in the binary image by repeating for a plurality of unit pixel blocks arranged in the first direction, and (b) for the array of pixel values rearranged in the step (a) A program for executing an image compression method including a procedure for performing compression by applying a predetermined lossless compression method, wherein the unit pixel block is in a second direction orthogonal to the first direction. And having a pixel column composed of a plurality of pixels.

  The invention of claim 2 is an image compression method for compressing a binary image, wherein (a) an operation of reading out pixel values of a plurality of pixels in each unit pixel block in the binary image in a predetermined order A step of reordering pixel values in the binary image by repeating for a plurality of unit pixel blocks arranged in the first direction in the value image; and (b) the pixel value reordered in step (a). Compressing the array by applying a predetermined lossless compression technique, and the unit pixel block is a pixel composed of a plurality of pixels in a second direction orthogonal to the first direction. It has a row.

  The invention according to claim 3 is an image compression apparatus for compressing a binary image, wherein an operation for reading out pixel values of a plurality of pixels in each unit pixel block in the binary image in a predetermined order is performed in the binary image. By repeating for a plurality of unit pixel blocks arranged in the first direction, a rearrangement unit that rearranges pixel values in the binary image, and an array of pixel values rearranged by the rearrangement unit, Compression means for applying a lossless compression method, and the unit pixel block has a pixel column composed of a plurality of pixels in a second direction orthogonal to the first direction. Features.

  The invention according to claim 4 is an image decompression device for decompressing a binary image compressed by a predetermined lossless compression technique, and (a) the image is compressed by using a decompression technique corresponding to the predetermined lossless compression technique. A decompression means for performing a decompression process on the binary image and generating a pixel string after the decompression process; and (b) arranging the pixel array after the decompression process at each predetermined position in each unit pixel block in the binary image. And rearranging means for restoring a plurality of unit pixel blocks arranged in the first direction in the binary image by repeating the rearrangement operation, wherein the unit pixel block is orthogonal to the first direction. In the second direction, a pixel column including a plurality of pixels is provided.

  According to the first to third aspects of the present invention, the compression ratio can be further improved by utilizing the regularity of the pixel columns in the second direction of the binary image.

  According to the fourth aspect of the present invention, it is possible to decode a binary image in a highly compressed state to the original state.

  Hereinafter, embodiments of the present invention will be described with reference to the drawings.

<A. System configuration>
<Overview>
FIG. 1 is a diagram illustrating a print system 1 according to an embodiment of the present invention. As shown in FIG. 1, the print system 1 includes a controller 10 and a printer 20. The controller 10 and the printer 20 are connected via a network NW such as a LAN.

  The controller 10 has a function of creating print output data for a file designated by the user and transmitting the data to the printer 20 via the network NW.

  The print output data is generated as data representing a binary image based on a file designated by the user. Specifically, even when the file to be printed includes a multi-valued image instead of a binary image, the binary data can be converted by performing a halftone process or the like on the data representing the multi-valued image. Data representing the image is generated. Further, the file to be printed is not limited to an image file, and may be a file including characters and the like. A file containing these characters and the like is converted into a binary image directly or once after being converted into a multi-valued image for printing output.

  The converted data representing the binary image becomes the processing target data in the compression processing described later. In other words, the binary image data for print output is compressed and transmitted to the printer 20. If the print target file originally represents a binary image, the binary image data may be used as compression processing target data as it is.

  The printer 20 is a device that performs print output based on data transmitted from the controller 10. The printer 20 performs decompression processing and rearrangement processing (described later) on the binary image data (compressed data) from the controller 10 to restore the original data, and performs print output based on the restored data. .

  The print output may be a monochrome image or a color image. When a monochrome image is printed, print output is performed based on a single binary image data. On the other hand, when printing a color image, binary images generated for each of a plurality of (for example, three) basic colors (for example, Y (yellow), M (magenta), and C (cyan)) are superimposed. By outputting, a color image can be printed out. Hereinafter, for the sake of simplification, printing of a monochrome image will be described. However, for a color image, it is possible to perform compression processing on each binary image for each basic color component.

  As will be described later, in the present system 1, the controller 10 functions as an image compression device, and the printer 20 functions as an image expansion device.

<Controller 10>
As shown in FIG. 1, the controller 10 includes a CPU 2, a main storage unit 3 a configured by a semiconductor memory such as a RAM (and / or ROM), and a storage unit 3 having an auxiliary storage unit 3 b such as a hard disk drive (HDD). A computer system (hereinafter simply referred to simply as a DVD drive) 4, a display unit 5 such as a liquid crystal display, an input unit 6 such as a keyboard 6a and a mouse 6b, and a communication unit 7 such as a network card. Also referred to as “computer”.

  The media drive 4 reads information recorded in a portable recording medium 9 such as a CD-ROM, DVD (Digital Versatile Disk), flexible disk, or memory card.

  The controller 10 implements various functions by reading a software program (hereinafter simply referred to as “program”) recorded on the recording medium 9 and executing the program using the CPU 2 or the like. Note that the program having each function is not limited to being supplied via the recording medium 9, and may be supplied to this computer via a network such as a LAN and the Internet.

  FIG. 2 is a diagram illustrating a software configuration and a functional unit block in the controller 10. FIG. 2A shows a software configuration in the controller 10, and FIG. 2B shows a functional configuration in the controller 10.

  As shown in FIG. 2A, on the controller 10, a predetermined operation system (basic software) OS, an application software program (hereinafter also simply referred to as “application software”) AS, and a printer driver PD operate. To do. Note that these operation system OS, application software AS, and printer driver PD are programs for realizing unique functions in each layer.

  When a file to be printed is selected in an application software AS (for example, word processing software) called on the operation system OS and a print output operation for the file is accepted, the application software AS performs a print output process for the file. Start. Then, the application software AS uses the printer driver PD corresponding to the printer 20 to generate print output data suitable for the printer 20 and transmits the print output data to the printer 20 via the network. An image compression function (described later) including rearrangement processing is implemented in the printer driver PD, and compressed binary image data (print output data) is transmitted from the controller 10 to the printer 20.

  Further, as shown in the functional block diagram of FIG. 2B, the controller 10 includes a rearrangement processing unit 11, a compression unit 12, and a transmission unit 13. The rearrangement processing unit 11 is a processing unit that performs processing (described later in detail) to rearrange binary image data according to a predetermined rule, and the compression unit 12 performs processing to compress the rearranged binary image data. Part. The transmission unit 13 is a processing unit that transmits the compressed data to the controller 10.

<Printer 20>
As shown in FIG. 1, the printer 20 includes a reception unit 21, an expansion unit 22, a rearrangement processing unit 23, an output control unit 24, and a print output unit 25. The receiving unit 21 is a processing unit that receives binary image data (compressed state) transmitted from the controller 10. The decompression unit 22 is a processing unit that decompresses data of a binary image in a compressed state (also referred to as “decompression” or “decoding”). It is a processing unit that performs a process of rearranging according to (rule) (detailed later). The print output unit 25 is a processing unit that performs print output based on the restored data, and the output control unit 24 is a processing unit that controls the print output.

<B. Outline of operation>
Next, a compression operation including rearrangement of binary images will be described with reference to FIG. FIG. 3 is a flowchart showing an operation performed by the controller 10.

  As shown in FIG. 3, first, a binary image is acquired in step SP11.

  More specifically, as described above, when the application software AS on the controller 10 receives a print output operation for a file to be printed, the application software AS delivers the file to be printed to the printer driver PD. The printer driver PD generates a binary image by performing bitmap development or halftone processing on the print target file.

  Next, in step SP12, rearrangement processing (detailed later) is performed on the binary image. This rearrangement process is performed by the rearrangement processing unit 11. Note that this rearrangement process is also expressed as a preprocess performed in the previous stage of the compression process in the next step SP13.

  In step SP13, the rearranged binary image data is compressed using a predetermined lossless compression method. This compression processing is performed by the compression unit 12 using a lossless compression method such as a universal encoding method (for example, LZ method).

  As will be described later, before applying a predetermined lossless compression method to a binary image, a reordering process is performed in advance in step SP12, thereby increasing the number of appearances of a repetitive pattern and compressing and encoding. The compression rate can be improved.

  Thereafter, in step SP14, the compressed data is transmitted to the printer 20 by the transmission unit 13 via the network NW.

  Next, a binary image expansion operation and the like will be described with reference to FIG. FIG. 4 is a flowchart showing operations performed by the printer 20.

  As shown in FIG. 4, first, when the receiving unit 21 (FIG. 1) of the printer 20 acquires binary image data in a compressed state (step SP21), the decompressing unit 22 converts the binary image data into a compressed state. The expansion process is performed on the area (step SP22). By this decompression processing, data that is completely the same as the data immediately before the compression processing in step SP13 is obtained. Thereafter, the rearrangement processing unit 23 performs a rearrangement process of the pixel columns (step SP23). The rearrangement process in step SP23 corresponds to the rearrangement method in step SP12. By this rearrangement process, binary image data in step SP11, in other words, binary image data immediately before the rearrangement process in step SP12, Is fully restored. This rearrangement process is also expressed as a post process performed at a later stage of the decompression process in step SP22.

  Thereafter, based on the restored data, printing output using the printing output unit 25 is performed under the control of the output control unit 24 (step SP24). As a result, a binary image is output on the printing paper.

<C. Processing during compression>
<Overview>
Next, the image compression process including the rearrangement process will be described in detail with a focus on the rearrangement process in step SP12.

  FIG. 5 is a diagram illustrating an example of a print output result of a character file. As described above, such a print output result is also realized as a binary image that has undergone halftone processing or the like.

  FIG. 6A corresponds to a diagram illustrating a state in which a part of the binary image is enlarged. In FIG. 6A, each pixel is represented by a minimum square, and a plurality of pixels are two-dimensionally arranged in two directions (horizontal direction and vertical direction) orthogonal to each other. Note that the binary image is formed with its constituent pixels arranged two-dimensionally, but the data representing the binary image may be configured as a one-dimensional array. Even in that case, the position (x, y) of each pixel in the horizontal direction and the vertical direction is specified by (virtually) folding back the pixel row of the one-dimensional array based on the total number of pixels (width) in the horizontal direction. It is possible.

  Further, as shown in FIG. 6A, the binary image expresses the pixel value (gradation value) of each pixel in the image with two-stage values. In the figure, the pixel value (gradation value) of each pixel of the binary image is either “0” or “1”, and the pixel value “0” is indicated by a white square. A pixel having a pixel value “1” is indicated by a hatched square. Here, for simplification of description, a case where rearrangement processing, compression processing, and the like are performed on a total of 128 pixels arranged in 16 pixels in the horizontal direction (X direction) and 8 pixels in the vertical direction (Y direction) will be described. To do. An actual image often has a further spread in the horizontal direction and the vertical direction, but the same processing may be repeated as appropriate.

  If rearrangement is not performed, assuming that the horizontal direction (X direction) is the main scanning direction and the vertical direction (Y direction) is the sub-scanning direction, the pixels are arranged in the order shown in FIG. Pixel values are read out to generate a one-dimensional array of pixel values totaling 128 pixels. Numbers 0, 1, 2,... Attached to each pixel in FIG. 6 are numbers indicating the arrangement order after the one-dimensional array conversion.

  Then, it is conceivable to compress the binary image by applying compression processing to the one-dimensional array of pixel values by a predetermined lossless compression method. In this case, as a result, a repetitive pattern of pixels appearing due to the regularity of the pixel column in the horizontal direction (X direction) of the binary image is used and compressed efficiently. However, the regularity of the pixel columns in the vertical direction (Y direction) of the binary image is hardly used.

  On the other hand, according to the following technique, it is possible to further improve the compression rate by utilizing the regularity of the pixel columns in the vertical direction. Below, such a technique is demonstrated.

  Specifically, first, (i) a binary image is divided into unit pixel blocks B having a predetermined pixel size. As will be described below, the unit pixel block B has a pixel column composed of a plurality of pixels in the sub-scanning direction (Y direction in this case) of the binary image (see FIGS. 7 to 9 and the like). reference). Then, (ii) an operation of reading pixel values of a plurality of (here, eight) pixels in the unit pixel block in the binary image in a predetermined order is arranged in the main scanning direction (here, the X direction) in the binary image. By repeating for a plurality of unit pixel blocks, the pixels in the binary image are rearranged, and (iii) a predetermined lossless compression technique is applied to the rearranged pixel columns to perform compression processing.

  Below, this rearrangement process etc. are demonstrated in detail. Various types of unit pixel blocks can be used, but here, the unit pixel block B has the following three types of rectangular shapes, that is, ((number of pixels in the horizontal direction). P) × (number of pixels Q in the vertical direction)) = (4 × 2), (2 × 4), and (1 × 8) are sequentially illustrated as examples.

<Part 1>
FIG. 7 is a diagram for explaining an example of the rearrangement process in the system 1. FIG. 7 is also the same diagram as FIG. 6, FIG. 7A shows a partially enlarged view of a binary image, and FIG. 7B shows a pixel column after rearrangement. However, the numbers in the pixels are different between FIG. 6A and FIG. This also appears as a difference between FIG. 6B and FIG. 7B regarding the pixel row after rearrangement.

  As shown in FIG. 7A, first, as a unit pixel block B, a pixel block including eight pixels having a size of 4 pixels (horizontal direction) × 2 pixels (vertical direction) (enclosed by a thick black frame in the drawing). Area). The unit pixel block B in FIG. 7A has a pixel size of 2 in the sub-scanning direction, and has a pixel column composed of two pixels in the sub-scanning direction.

  Then, the rearrangement processing unit 11 reads out the pixel values of the eight pixels in the first unit pixel block B in a predetermined order. Here, first, the upper four pixels arranged in the horizontal direction in the binary image (see FIG. 7A) are sequentially read from left to right, and then the lower four pixels arranged on the lower side are read. The case of reading sequentially from left to right is illustrated. Thus, the eight pixels of numbers 0 to 7 are read in this order. As a result, as shown in FIG. 7B, a one-dimensional array relating to the pixel values of the eight pixels numbered 0 to 7 is formed.

  Next, the same readout operation is repeated for a plurality of unit pixel blocks B arranged continuously in the main scanning direction (X direction) in the binary image.

  Specifically, the eight pixels in the numbers 8 to 15 are read in this order by similarly reading the eight pixels in the next (right adjacent) unit pixel block. Further, by reading out the eight pixels in the next unit pixel block in the same manner, the pixels of numbers 16 to 23 are read out in this order.

  Further, when the reading of the unit pixel block at the end position in the main scanning direction (for example, including the pixels of numbers 24 to 31) is completed, the same operation is repeated by moving one block in the sub scanning direction (Y direction). It is. Specifically, the process proceeds to the unit pixel block immediately below the read unit pixel block at the start position in the main scanning direction (for example, including the pixels of numbers 32 to 39), and the same applies to each unit pixel block in the main scanning direction. The reading operation may be continued.

  Similarly, by repeating the reading operation for each unit pixel block, all the pixels (128 pixels in this case) are read out as a one-dimensional pixel array (data string) from number 0 to number 127.

  The above process is executed in step SP12.

  Thereafter, the compression process of step SP13 is executed. Specifically, a compression process using a predetermined lossless compression method is performed on the rearranged data string. The pixel value of each pixel may be handled as it is in 1-bit units, and compression processing may be performed. However, here, the pixel values of each pixel represented by each 1-bit are grouped by 8 one byte (8 It is handled as information in bits) and is subjected to compression processing.

  More specifically, (1) the first one-byte character (“10011001” in binary notation) that summarizes the pixel values of pixels numbered 0 to 7, and (2) the pixel values of pixels numbered 8 to 15 Next 1 byte character (“00000000” in binary notation), (3) Next 1 byte character (“00000000” in binary notation) that summarizes the pixel values of numbers 16 to 23, (4 ) The next 1-byte character that summarizes the pixel values of the pixels of numbers 24 to 31 (binary representation “00010010”), (5) The next 1-byte character that summarizes the pixel values of the pixels of numbers 32 to 39 A character string composed of a plurality of 1-byte characters including (1011101 in binary notation),...

  As the lossless compression method, for example, the LZ method developed by Abraham Lempel and Jacob Ziv et al. May be used. The LZ method includes LZ77, LZ78, and various improved methods thereof (for example, LZSS method, LZW method, etc.). Further, the lossless compression method is not limited to the LZ method, and various methods such as a run length method, a partial match prediction method, and a block sorting method can be used.

  In the above, pixels existing at a position close in the sub-scanning direction of the binary image are arranged at a position close in the one-dimensional array after the rearrangement.

  For example, the pixels of numbers 8 to 11 and the pixels of numbers 12 to 15 below the pixels are arranged close to each other after rearrangement (see FIG. 7). This is in contrast to the fact that each pixel numbered 4-7 in FIG. 6 and each pixel numbered 20-23 below are arranged apart from each other after rearrangement.

  In other words, the one-dimensional array after rearrangement in FIG. 7B reflects the correlation or regularity in the sub-scanning direction in the binary image (in particular, the continuity in the vertical direction in the binary image here). It has become. More specifically, a predetermined repetitive pattern “00000000” in which “0” continues is understood as compared with the pixel row (b) of numbers 0 to 31 in FIG. 7B and the same pixel row in FIG. , Have been rearranged to appear more. Specifically, the pixel columns of Nos. 8 to 15, the pixel columns of Nos. 16 to 23, the pixel columns of Nos. 40 to 47, and the like are all “00000000”. In short, in a binary image, it can also be expressed that white areas (for example, background portions) divided by black portions (for example, character portions) will be arranged together by the rearrangement process. Thus, it can be seen that the one-dimensional data after rearrangement is in a state of being easily compressed.

  Thus, the one-dimensional data after the rearrangement uses the regularity of the pixel columns in the “sub-scanning direction” of the binary image (in other words, the geometric property that the binary image has a two-dimensional spread). The compression ratio is rearranged so that the compression rate can be further improved.

<Part 2>
FIG. 8 is a diagram illustrating another rearrangement process. 8 is also a view similar to FIGS. 6 and 7, FIG. 8A shows a partially enlarged view of a binary image, and FIG. 8B shows a pixel row after rearrangement. However, the numbers in the pixels are different between FIG. 8A and FIG. This also appears as a difference between FIG. 8B and FIG. 7B regarding the pixel column after rearrangement.

  In FIG. 8, as the unit pixel block B, a pixel block including 8 pixels of 2 pixels (horizontal direction) × 4 pixels (vertical direction) (a region surrounded by a thick black frame in the drawing) is assumed. The unit pixel block B in FIG. 8A has a pixel size of 4 in the sub-scanning direction, and has a pixel column composed of four pixels in the sub-scanning direction.

  Then, the pixel values of the eight pixels in the unit pixel block B are read in a predetermined order. Here, first, the top two pixels arranged in the horizontal direction are continuously read out, then the two pixels in the second row immediately below it, two pixels in the third row, and finally the fourth pixel in the fourth row The case where two pixels are read sequentially is illustrated. Thus, the eight pixels of numbers 0 to 7 are read in this order.

  Next, the same readout operation is repeated for a plurality of unit pixel blocks B arranged repeatedly in the main scanning direction (X direction) in the binary image. Further, when the reading in the main scanning direction is completed to the end position, the unit pixel block is moved in the Y direction length (here, 4 pixels) in the Y direction, and the same operation is repeated. As a result, all pixels (128 pixels in this case) are read out as a one-dimensional pixel array from number 0 to number 127.

  Here, the one-dimensional array after the rearrangement reflects the continuity in the vertical direction in the binary image. For example, the pixel column numbered 16 to 23, the pixel column numbered 24 to 31, and the pixel column numbered 32 to 39 are all “00000000”. In other words, rearrangement is performed so that more predetermined repeated patterns with consecutive “0” appear. Therefore, it can be seen that the one-dimensional data after rearrangement is easily compressed.

  After the above processing is executed in step SP12, the rearranged data string is compressed by a predetermined lossless compression method (step SP13).

  Here, it is assumed that eight pixel values of each pixel represented by each 1 bit are collected and handled as 1-byte (8-bit) information and subjected to compression processing. More specifically, (1) the first one-byte character (“10101011” in binary notation) that summarizes the pixel values of pixels numbered 0 to 7, and (2) the pixel values of pixels numbered 8 to 15 The next single byte character (“01011011” in binary representation), (3) the next single byte character (“00000000” in binary representation) that summarizes the pixel values of numbers 16 to 23, (4 ) Next 1-byte character that summarizes the pixel values of the pixels numbered 24 to 31 (binary representation “00000000”), (5) Next 1-byte character that summed the pixel values of the pixels numbered 32 to 39 (Binary representation “00000000”),... (Hereinafter the same), a character string composed of a plurality of 1-byte characters is compressed.

<Part 3>
FIG. 9 is a diagram for explaining still another rearrangement process. FIG. 9 is also a view similar to FIGS. 6 to 8, FIG. 9A shows a partially enlarged view of a binary image, and FIG. 9B shows a pixel row after rearrangement. However, the numbers in the pixels are different between FIG. 9A and FIG. This also appears as a difference between FIG. 9B and FIG. 7B regarding the pixel column after rearrangement.

  9, a unit pixel block B is assumed to be a pixel block including eight pixels of 1 pixel (horizontal direction) × 8 pixels (vertical direction) (a region surrounded by a thick black frame in the drawing). The unit pixel block B in FIG. 9A has a pixel size of 8 in the sub-scanning direction, and has a pixel column composed of 8 pixels in the sub-scanning direction.

  Then, the pixel values of the eight pixels in the unit pixel block B are read in a predetermined order. Here, a case where reading is sequentially performed from the top to the bottom according to the order arranged in a line in the vertical direction is illustrated. Thus, the eight pixels of numbers 0 to 7 are read in this order.

  Next, the same readout operation is repeated for a plurality of unit pixel blocks B arranged repeatedly in the main scanning direction (X direction) in the binary image. As a result, all pixels (128 pixels in this case) are read out as a one-dimensional pixel array from number 0 to number 127.

  Here, the one-dimensional array after the rearrangement reflects the continuity in the vertical direction in the binary image. For example, the pixel column numbered 32 to 39, the pixel column numbered 40 to 47, the pixel column numbered 48 to 55, etc. are all “00000000”. In other words, rearrangement is performed so that more predetermined repeated patterns with consecutive “0” appear. Therefore, it can be seen that the one-dimensional data after rearrangement is easily compressed.

  After the above processing is executed in step SP12, the rearranged data string is compressed by a predetermined lossless compression method (step SP13).

  Here, it is assumed that eight pixel values of each pixel represented by each 1 bit are collected and handled as 1-byte (8-bit) information and subjected to compression processing. More specifically, (1) the first 1-byte character (“11111111” in binary notation) that summarizes the pixel values of pixels numbered 0 to 7, and (2) the pixel values of pixels numbered 8 to 15 The next single byte character (binary representation “00010000”), (3) the next single byte character summarizing the pixel values of numbers 16 to 23 (binary representation “00100000”), (4 ) Next 1-byte character that summarizes the pixel values of the pixels numbered 24 to 31 (binary expression “11111111”), (5) Next 1-byte character that summed the pixel values of the pixels numbered 32 to 39 (Binary representation “00000000”),... (Hereinafter the same), a character string composed of a plurality of 1-byte characters is compressed.

<Summary>
FIG. 10 is a diagram conceptually showing the above-described rearrangement process. Each of the three types of unit pixel blocks B (FIGS. 7 to 9) is configured by a rectangular pixel array in which Z pixels are arranged in the horizontal direction and (8 / Z) pixels are arranged in the vertical direction (Z = 4, 2, 1). Then, by reading the pixel values of the respective pixels in the unit block in a predetermined order, continuous 8-bit (1 byte) data is generated after the rearrangement.

  As shown in FIG. 10, in the first example (see FIG. 7, Z = 4), this corresponds to rearranging the pixels so that the original binary image is stretched twice in the horizontal direction and half in the vertical direction. To do. In the next example (see FIG. 8, Z = 2), this corresponds to rearranging the pixels so that the original binary image is expanded four times in the horizontal direction and reduced to ¼ in the vertical direction. In the last example (see FIG. 9, Z = 1), this corresponds to rearranging the pixels so that the original binary image is stretched 8 times in the horizontal direction and compressed to 1/8 in the vertical direction. In any case, the total number of pixels is the same before and after the pixel rearrangement.

  Thus, since the pixel information in the vertical direction can be expanded in the horizontal direction, it is possible to make more repetitions of the same pattern appear using the regularity in the vertical direction of the binary image. Therefore, it is possible to further increase the degree of compression in the subsequent compression stage (improve the compression rate).

<D. Processing during expansion>
Next, image expansion processing in the printer 20 will be described.

  First, in step SP22, decompression is performed by applying a decompression method corresponding to a predetermined lossless image compression method. For example, when compression processing is performed using the LZSS method, decompression processing using the LZSS method is performed. Which method should be used may be determined in advance. By the decompression process in step SP22, data completely identical to the data immediately before the compression process in step SP13 is obtained.

  Next, in step SP23, the rearrangement processing unit 23 repeats the operation of arranging and rearranging the expanded pixel columns at respective predetermined positions in the unit pixel block based on a predetermined arrangement rule, thereby repeating the binary image. A plurality of unit pixel blocks arranged in the horizontal direction are restored. By this rearrangement process, the binary image data before the compression process in the controller 10 (binary image data immediately before the rearrangement process in step SP12) is completely restored.

  More specifically, the rearrangement processing unit 23 rearranges the expanded pixel columns in accordance with a predetermined unit pixel block type and the arrangement order in the unit pixel block type to restore the original pixel columns.

  For example, when it is determined in advance that the unit pixel block type and the arrangement order in the unit pixel block are those shown in FIG. 7, the printer 20 follows FIG. 7 ( The expanded pixel columns as shown in b) may be rearranged in the arrangement order of FIG. As a result, the uppermost pixel row is composed of pixels of numbers 0 to 3, 8 to 11, 16 to 19, and 24 to 27, and pixels of numbers 4 to 7, 12 to 15, 20 to 23, and 28 to 31 are formed. A pixel row in the next stage can be configured. Thereafter, in the same manner, the entire pixel column can be restored.

  According to such processing, it is possible to return a binary image in a highly compressed state to its original state.

  Here, the case where the original binary image is restored according to a predetermined rearrangement order or the like is illustrated, but the present invention is not limited to this, and the type of unit pixel block used at the time of compression is determined as the header of the compressed file. The information may be stored in the information, and the printer 20 may perform rearrangement processing (step SP23) according to the contents of the header information.

<E. Other>
As described above, the controller 10 of the system 1 assumes that (i) a unit pixel block having a pixel size of 2 or more in the sub-scanning direction (Y direction) as a unit pixel block that classifies a binary image, (ii) ) By repeating the operation of reading the pixel values of a plurality (eight) pixels in each unit pixel block in a predetermined order for a plurality of unit pixel blocks arranged in the main scanning direction in the binary image, a binary image is obtained. (Iii) A predetermined lossless compression technique is applied to the rearranged pixel column to perform compression processing. Therefore, the compression processing is performed after rearranging in consideration of the regularity of the pixel columns in the vertical direction, so that the compression rate can be further improved.

  In addition, when comparing the LZSS method and the LZW method of the LZ method, the above concept involving rearrangement is generally applied to the LZSS method (although depending on the difference in the target image and the content of the halftone processing). When applied, the compression rate improvement effect due to the rearrangement is higher than when the above idea is applied to the LZW method. This is considered to be based on a difference in dictionary structure in which the LZW method creates a wide-area dictionary while the LZSS method uses the latest data string as a dictionary.

  Moreover, it is preferable to adopt an appropriate value according to the compression method as the aspect ratio (in other words, the value of Z) of the unit pixel block at the time of rearrangement. For example, for some images, the effect of improving the compression ratio is enhanced when Z = 1 or Z = 2 in the LZSS method, and when Z = 2 or Z = 4 in the LZW method. There is a tendency that the effect of improving the compression ratio is increased. Note that the improvement effect of the compression ratio also varies depending on the difference in the target image and the difference in the halftone processing content. Is preferred.

  Moreover, in the said embodiment, although the case shown in FIGS. 7-10 was illustrated as a reading order in a unit pixel block, it is not limited to this. Specifically, the reading order as shown in FIGS. 11 and 12 may be used. FIG. 11 and FIG. 12 are diagrams showing partially enlarged views similar to FIG. 7A and the like for various modified examples. The numbers given to the respective pixels are the numbers of the respective pixels in the unit pixel block. Indicates the reading order.

  FIG. 11 is a diagram illustrating various modified examples of reading out pixel values in a different order from FIG. 7 for the unit pixel block B corresponding to Z = 4.

  Specifically, in FIG. 11A, among the pixels in the unit pixel block B extending in the upper and lower two stages, the upper pixel and the lower pixel are alternately read out in this order for each vertical pixel column in the horizontal direction (X An example in which the pixel values of all the pixel columns are read while sequentially moving in the direction). FIG. 11B shows the pixel values of eight pixels starting from the pixel value of the 0th pixel at a predetermined position in the unit pixel block B and rotating around the predetermined direction (counterclockwise here). An example of reading is illustrated.

  FIG. 12 is a diagram showing various modifications for reading out pixel values in a different order from FIG. 8 for the unit pixel block B corresponding to Z = 2.

  Specifically, in FIG. 12A, among the two vertical pixel columns extending in four stages in the vertical direction (Y direction), first, the pixel values of the four pixels in the left vertical pixel line are directed from the top to the bottom. An example will be described in which reading is performed in accordance with the arrangement order, and then four pixels in the right vertical pixel column are read out in accordance with the arrangement order from the top to the bottom. FIG. 12B shows a horizontal pixel row of two pixels arranged in four stages from the top to the bottom, and the reading order for each stage (from left to right, from right to left). An example of reading while changing alternately will be described. Further, FIG. 12C shows a case where pixel values of eight pixels are read out in a predetermined direction (clockwise in this case) starting from the pixel value of the 0th pixel located at a predetermined position in the unit pixel block B. Is illustrated.

  Furthermore, the pixel value of each pixel in the unit pixel block B may be read using a reading order other than this.

  In the above embodiment, the unit pixel block B is configured by 8 pixels. However, the present invention is not limited to this. For example, the unit pixel block B may be configured by 16 pixels. .

  Further, in the above-described embodiment, the case where the one-dimensional array after the rearrangement is subjected to the compression process after the pixels are collectively treated as one-byte characters is illustrated, but the present invention is not limited to this. For example, 16 pixels may be collectively handled in units of 2 bytes (16 bits) and subjected to compression processing. Alternatively, the compression processing may be performed by collectively handling four pixels in units of 4 bits. Furthermore, as described above, the pixel value of each pixel may be handled as it is in 1-bit units and subjected to compression processing.

  Moreover, although the case where the horizontal direction (X direction) is the main scanning direction is illustrated in the above embodiment, the present invention is not limited to this. For example, contrary to the above, the vertical direction (Y direction) may be the main scanning direction and the horizontal direction (X direction) may be the sub-scanning direction. In other words, a plurality of unit pixel blocks may be read sequentially in the vertical direction first. In this case, each unit pixel block may be configured to have a pixel column composed of a plurality of pixels in the sub-scanning direction (X direction) of the binary image. In short, the pixel size in the sub-scanning direction (X direction) in each unit pixel block may be 2 or more.

  Furthermore, in the above-described embodiment, the case where data is transferred using the network NW has been exemplified. However, the present invention is not limited to this, and the data compression for performing various data transfer such as data transfer via a parallel port is described above. Thoughts may be applied. Even in this case, it is possible to improve the efficiency of data transfer by improving the compression rate.

  In the above embodiment, the case where the above idea is applied to the compression of the binary image for print output has been described. However, the invention is not limited to this, and the above idea is applied to a binary image for other purposes. Also good. According to this, it is possible to improve data storage efficiency (for example, save memory area or save hard disk area) by improving the compression rate.

1 is a diagram illustrating a schematic configuration of a print system. It is a figure which shows the software configuration and functional block of a controller. It is a flowchart which shows operation | movement of a controller. 3 is a flowchart illustrating an operation of a printer. It is a figure which shows an example of the print output result of a character file. It is a figure which shows the state etc. (comparative example) which expanded a part of binary image. It is a figure explaining an example of a rearrangement process. It is a figure explaining another rearrangement process. It is a figure explaining another rearrangement process. It is a figure which shows the rearrangement process notionally. It is a figure which shows the modification of a rearrangement order. It is a figure which shows the modification of a rearrangement order.

Explanation of symbols

1 Print System 4 Media Drive 9 Recording Medium 10 Controller 20 Printer B Unit Pixel Block NW Network

Claims (4)

On the computer,
(a) By repeating an operation of reading pixel values of a plurality of pixels in each unit pixel block in the binary image in a predetermined order for a plurality of unit pixel blocks arranged in the first direction in the binary image. Reordering the pixel values in the binary image;
(b) a procedure for compressing the array of pixel values rearranged in the procedure (a) by applying a predetermined lossless compression method;
A program for executing an image compression method including:
The unit pixel block has a pixel column composed of a plurality of pixels in a second direction orthogonal to the first direction. An image compression method for compressing a binary image,
(a) By repeating an operation of reading pixel values of a plurality of pixels in each unit pixel block in the binary image in a predetermined order for a plurality of unit pixel blocks arranged in the first direction in the binary image. Reordering pixel values in the binary image;
(b) compressing the array of pixel values rearranged in step (a) by applying a predetermined lossless compression technique;
Including
2. The image compression method according to claim 1, wherein the unit pixel block has a pixel row composed of a plurality of pixels in a second direction orthogonal to the first direction. An image compression device for compressing a binary image,
By repeating the operation of reading the pixel values of a plurality of pixels in each unit pixel block in the binary image in a predetermined order for the plurality of unit pixel blocks arranged in the first direction in the binary image, Rearrangement means for rearranging pixel values in the value image;
Compression means for compressing an array of pixel values rearranged by the rearrangement means by applying a predetermined lossless compression technique;
With
The image compressing apparatus according to claim 1, wherein the unit pixel block includes a pixel column composed of a plurality of pixels in a second direction orthogonal to the first direction. An image expansion device that expands a binary image compressed by a predetermined lossless compression method,
(a) using a decompression technique corresponding to the predetermined lossless compression technique, decompression means for performing a decompression process on the compressed binary image and generating a pixel string after the decompression process;
(b) The pixel row after the decompression process is arranged in the first direction in the binary image by repeating the operation of arranging and rearranging the pixel row at each predetermined position in each unit pixel block in the binary image. Reordering means for restoring a plurality of unit pixel blocks;
With
The image expansion apparatus according to claim 1, wherein the unit pixel block has a pixel column composed of a plurality of pixels in a second direction orthogonal to the first direction.

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