JP2006270174A - Coder, decoder, coding method, decoding method, and programs thereof - Google Patents

Abstract

<P>PROBLEM TO BE SOLVED: To provide a coder and a decoder capable of improving the reproducibility of minute edges of input image. <P>SOLUTION: A coding program 4 includes a multi-value data generating section 402; a dot data generating section 404; an edge detection section 406; a correction data generating section 408, and a code generating section 410. The multi-value data generating section 402 converts a binary input image into multi-value image data, having resolution lower than that of the input image. The dot data generating section 404 generates identification data for identifying a non-edge part of the multi-value image, on the basis of the multi-value image data. The edge detection section 406 detects an image part, corresponding to the edge on the basis of the multi-value image data. The correction data generating section 408 selects the edge image of the input image, on the basis of the detected edge part. The code-generating section 410 codes the non-edge image and the edge image independently, to generate code data. <P>COPYRIGHT: (C)2007,JPO&INPIT

Description

  The present invention relates to an encoding device that encodes a binary image, and more particularly to an encoding device that encodes a binary image having edges.

For example, Non-Patent Document 1 discloses JBIG2 that efficiently encodes image elements. JBIG2 defines a halftone region, a generic region, a text region encoding process, a refinement region, and the like.
However, Non-Patent Document 1 does not consider an encoding process and a decoding process that can reproduce a fine edge of an image.

ITU-T Recommendation T.88 (02/00), “Lossy / lossless coding of bi-level images”, [online], 1999, ITU-T, [searched on February 21, 2005], Internet < URL: http://www.itu.int/rec/recommendation.asp?type=folders&lang=e&parent=T-REC-T.88>

  The present invention has been made from the above-described background, and an object thereof is to provide an encoding device and a decoding device capable of improving the reproducibility of fine edges of a halftone image.

  To achieve the above object, an encoding apparatus according to the present invention identifies edge image generation means for generating an edge image corresponding to an edge portion of an input binary image and a non-edge portion of the binary image. Identification data generating means for generating identification data, edge data generated by the edge image generating means, and encoding means for encoding the identification data generated by the identification data generating means by different methods .

Preferably, the image processing apparatus further includes edge detection means for detecting an edge of the binary image, and the edge image generation is based on an image portion corresponding to the edge detected by the edge detection means and a binary image. Generate an edge image.
Preferably, the identification data generating means includes a multi-value image generating means for generating a multi-value image having a lower resolution from the input binary image, and a multi-value image generated by the multi-value image generating means. Halftone dot pattern generation means for generating a binary halftone dot pattern representing gradation.
Preferably, the encoding unit encodes the halftone dot pattern generated by the halftone dot pattern generation unit in association with the position in the multilevel image generated by the multilevel image generation unit.

  In addition, the decoding apparatus according to the present invention includes an edge image decoding unit that decodes an edge image corresponding to an edge portion of an encoded binary image, based on the code data, and identification data included in the code data A non-edge image decoding means for decoding a non-edge image corresponding to a non-edge portion of a binary image, an edge image decoded by the edge image decoding means, and the non-edge image decoding Image generating means for generating a binary image based on the non-edge image decoded by the means.

  Preferably, the image generation means performs an OR operation between the edge image decoded by the edge image decoding means and the non-edge image decoded by the non-edge image decoding means, A binary image is generated.

  The encoding method according to the present invention generates an edge image corresponding to an edge portion of an input binary image, generates identification data for identifying a non-edge portion of the binary image, and generates the generated edge. The image and the generated identification data are encoded by different methods.

  Further, the decoding method according to the present invention decodes an edge image corresponding to an edge portion of an encoded binary image based on code data, and outputs a binary image based on identification data included in the code data. A non-edge image corresponding to the non-edge portion of the image is decoded, and a binary image is generated based on the decoded edge image and the decoded non-edge image.

  The first program according to the present invention includes an edge image generation step for generating an edge image corresponding to an edge portion of an input binary image and a non-edge portion of the binary image in an encoding device including a computer. An identification data generation step for generating identification data for identifying the image, and an encoding step for encoding the generated edge image and the generated identification data by different methods are executed in the computer of the encoding device Let

  Further, the second program according to the present invention provides an edge image decoding step of decoding an edge image corresponding to an edge portion of an encoded binary image based on code data in a decoding device including a computer. A non-edge image decoding step for decoding a non-edge image corresponding to a non-edge portion of the binary image based on identification data included in the code data, the decoded edge image, and the decoding An image generation step for generating a binary image based on the processed non-edge image and a computer of the decoding apparatus are executed.

  According to the encoding apparatus of the present invention, it is possible to generate code data that can improve the reproducibility of fine edges of a halftone image.

First, in order to help understanding of the present invention, its background and outline will be described.
As a binary image encoding method, JBIG2 halftone region encoding has been proposed.
1A and 1B are diagrams for explaining a halftone area encoding process. FIG. 1A illustrates a binary image to be encoded, and FIG. 1B illustrates a halftone area encoding process. FIG. 1C illustrates code data generated using the image dictionary 700 and a decoded image 610 thereof.
As illustrated in FIG. 1A, a binary image element (in this example, a character image “A”) is composed of a plurality of halftone dot patterns corresponding to density values (tone values), and is simulated. Is expressed in gradation. The size of the halftone dot pattern corresponds to the density value. In this example, since the character image “A” has a uniform density, a halftone dot pattern of a uniform size constitutes the character image “A”. In the halftone area encoding process of JBIG2, these halftone dot patterns (binary values) are registered in the image dictionary 700 in association with density values, and a binary image composed of the halftone dot patterns is encoded.

As illustrated in FIG. 1B, when a plurality of halftone dot patterns having different sizes exist in the input image 600, each halftone dot pattern is associated with an index (density value), and the image dictionary 700 is used. Registered in This index is identification information for uniquely identifying each halftone dot pattern, and is a density value in this example.
When the input image 600 is encoded using the image dictionary 700, code data as illustrated in FIG. 1C is generated. The code data includes density values (that is, indexes) of the respective areas in the input image 600 and position information (grid-like positions) indicating positions where the density values exist.
This code data is decoded with reference to the image dictionary 700 to become a decoded image 610. Specifically, a halftone dot pattern registered in the image dictionary 700 is selected based on the code data (density value), and the selected halftone dot pattern is arranged according to the code data (position information). A decoded image 610 is generated.

FIG. 2 is a diagram illustrating an image dictionary 702 and a decoded image 612 when an input image 602 having an edge is encoded by a halftone region encoding process.
As illustrated in FIG. 2, when the density value that can be identified is three gradations, the image dictionary 702 identifies the non-edge portion of the binary image based on the character image “A” having an edge. The index 1 to be registered and the index 2 for identifying the edge portion can be registered. When the input image 602 is encoded by the halftone area encoding process, the edge information of the character image “A” may be lost in the decoded image 612.

[Image processing device]
FIG. 3 is a diagram illustrating an encoding process by the image processing apparatus 2 according to the present invention.
As shown in FIG. 3, binary correction data 620 (edge image) is further generated from the binary input image 602 in addition to position information (identification data) for identifying the non-edge portion. The binary correction data 620 is image data corresponding to the edge portion of the input image 602. The non-edge partial image 614 is identified based on position information of an image portion that is a predetermined density value or a range of density values, and identification data is generated.
The identification data is encoded by halftone region encoding, and the binary correction data 620 is encoded by generic region encoding to generate code data 900.

FIG. 4 is a diagram illustrating a decoding process by the image processing apparatus 2 according to the present invention.
As illustrated in FIG. 4, identification data (position information) included in the code data 900 is decoded in the halftone region, and a non-edge partial image 614 is generated. Also, based on the code data 900, the binary correction data 620 is generated by being compounded in the generic area. Further, based on the non-edge partial image 614 and the binary correction data 620, a decoded image 630 is generated using a refinement region defined by JBIG2. The refinement region is a region in which a known image is changed and an image different from this image is generated.
In this way, the reproducibility of fine edges of the character image “A” can be improved.

[First Embodiment]
An image processing apparatus 2 according to the first embodiment of the present invention will be described.

[Hardware configuration]
A hardware configuration of the image processing apparatus 2 in the present embodiment will be described.
FIG. 5 is a diagram illustrating a hardware configuration of the image processing apparatus 2 to which the encoding method and the decoding method according to the present invention are applied, centering on the control apparatus 20.
As illustrated in FIG. 5, the image processing apparatus 2 includes a control device 20 including a CPU 202 and a memory 204, a communication device 22, a storage device 24 such as an HDD / CD device, an LCD display device or a CRT display device, and a keyboard. A user interface device (UI device) 26 including a touch panel and the like is included.
The image processing device 2 is, for example, a general-purpose computer in which an encoding program 4 and a decoding program 5 described later are installed as part of a printer driver, and acquires image data via the communication device 22 or the storage device 24. The obtained image data is encoded or decoded and transmitted to the printer apparatus 10. Further, the image processing apparatus 2 may acquire image data optically read by the scanner function of the printer apparatus 10 and encode the acquired image data.

[Encoding program]
FIG. 6 is a diagram illustrating a functional configuration of the first encoding program 4 which is executed by the control device 20 (FIG. 5) and realizes the encoding method according to the present invention.
As illustrated in FIG. 6, the encoding program 4 includes a raster generation unit 400, a multi-value data generation unit 402, a halftone data generation unit 404, an edge detection unit 406, a correction data generation unit 408, and a code generation unit 410. The code generation unit 410 includes a non-edge information encoding unit 412 and an edge information encoding unit 414.
Note that all or some of the functions of the encoding program 4 may be realized by an ASIC provided in the printer apparatus 10 or the like.

  In the encoding program 4, the raster generation unit 400 acquires image data (input image 602) in PDL (Page Description Language) format acquired via the communication device 22 or the storage device 24, and the acquired input image 602 is output to the multi-value data generation unit 402 and the correction data generation unit 408.

  The multi-value data generation unit 402 converts the input image 602 input from the raster generation unit 400 into multi-value image data with a lower resolution, and outputs it to the halftone data generation unit 404 and the edge detection unit 406. More specifically, the multi-value data generation unit 402 converts a binary image expressed by, for example, two gradations of 0 value and 1 value to 3 gradations or more (for example, 256 gradations from 0 value to 255 values). Convert to multi-valued image data expressed by The multi-value processing will be described later.

The halftone data generation unit 404 specifies identification data (position information) for identifying a portion corresponding to the non-edge portion of the input image 602 based on the multi-value image data input from the multi-value data generation unit 402. The data is output to the code generation unit 410 together with the halftone data (density value). More specifically, an image portion having a predetermined density value (for example, 255) or a predetermined density value range (for example, 200 or more) is extracted from the density values included in the multivalued image data. The halftone dot data generation unit 404 uses the extracted image portion as position information and identifies non-edge portions in association with halftone dot data corresponding to the density value (or density value range).
In this way, the multi-value data generation unit 402 and the halftone data generation unit 404 constitute identification data generation means for generating identification data for identifying the non-edge portion of the binary image.

  The edge detection unit 406 detects an image portion corresponding to the edge portion of the input image 602 based on the multi-value image data input from the multi-value data generation unit 402 and outputs the image portion to the correction data generation unit 408. More specifically, an image portion having a predetermined density value (for example, 64, 128) or a predetermined density value range (for example, 64 or more and less than 200) is extracted from the density values included in the multivalued image data.

  The correction data generation unit 408 selects an image portion determined to be an image portion corresponding to the edge by the edge detection unit 406 from the input image 602 input from the raster generation unit 400, and other than the selected image portion. By setting the area to a predetermined pixel value (for example, 0), binary correction data 620 (FIG. 3) is generated. That is, the binary correction data 620 is image data including an edge portion of the input image 602 and a non-edge portion whose pixel value is set to 0, for example. The correction data generation unit 408 outputs the generated binary correction data 620 to the code generation unit 410.

The code generation unit 410 encodes the input image 602 based on the identification data generated by the halftone data generation unit 404 and the binary correction data generated by the correction data generation unit 408, and stores the code data 900 in a storage device. 24 (FIG. 5) or the printer device 10 or the like.
More specifically, the non-edge information encoding unit 412 is based on the identification data generated by the halftone data generation unit 404 (data for identifying the non-edge portion of the image element included in the input image 602 based on the position information). Thus, the non-edge information of the image element included in the input image 602 is encoded by the halftone area encoding specified by JBIG2.

The edge information encoding unit 414 encodes the binary correction data generated by the correction data generation unit 408 by generic region encoding defined in JBIG2.
Note that the non-edge information encoding unit 412 and the edge information encoding unit 414 may encode respective encoding targets by entropy encoding (Huffman encoding, arithmetic encoding, LZ encoding, or the like).

FIG. 7 is a diagram exemplifying multi-value conversion processing by the multi-value data generation unit 402.
As illustrated in FIG. 7, the multi-value data generation unit 402 converts a binary image expressed with two gradations into multi-value image data expressed with three or more gradations. For example, the multi-value data generation unit 402 sets the 0 value included in the binary image to the 0 value as it is, sets the 1 value included in the binary image to the 255 value, and further sets a predetermined value corresponding to the resolution in the main scanning direction. The pixel of interest is selected at intervals, and multivalue conversion is performed by calculating an average value of pixel values (0 or 255) of a peripheral region (for example, a 2 × 2 pixel size region) including the pixel of interest.

[Code data]
FIG. 8 is a diagram illustrating code data generated by the encoding program 4 (FIG. 6).
As illustrated in FIG. 8, code data includes a header including data attribute information and the like, a halftone area code corresponding to identification data (position information, etc.) indicating a non-edge portion of an image element, and binary data. And a generic region code corresponding to the correction data 620. The halftone area code includes position information indicating an area where a halftone dot pattern (density value) corresponding to a non-edge portion of an image element exists. The generic area code includes code data obtained by encoding the binary correction data 620.

[Encoding operation]
FIG. 9 is a flowchart showing the encoding process (S10) by the encoding program 4.
As shown in FIG. 9, in step 100 (S100), when a PDL file is input as an input image, the raster generation unit 400 converts a binary input image 602 into a multi-value based on the input PDL file. The data is output to the data generation unit 402 and the correction data generation unit 408.
The multi-value data generation unit 402 converts the character image input from the raster generation unit 400 into multi-value image data having a lower resolution, and outputs the multi-value data to the halftone data generation unit 404 and the edge detection unit 406.

  In step 102 (S102), the halftone data generation unit 404 extracts the density value corresponding to the non-edge portion based on the multi-value image data input from the multi-value data generation unit 402, and determines the density value of the density value. Identification data is generated from the position information of the image portion and output to the non-edge information encoding unit 412.

In step 104 (S104), the edge detection unit 406 detects the density value corresponding to the edge portion based on the multi-value image data input from the multi-value data generation unit 402, and the image portion of this density value The position information is output to the correction data generation unit 408.
In step 106 (S106), the correction data generation unit 408 selects the edge portion input from the edge detection unit 406 from the character image input from the raster generation unit 400, and predetermines a region other than the selected image portion. Binary correction data is generated by setting the pixel value to. The correction data generation unit 408 outputs the generated binary correction data to the edge information encoding unit 414.

In step 108 (S108), the non-edge information encoding unit 412 encodes the identification data input from the halftone data generation unit 404 by halftone region encoding.
In step 110 (S110), the edge information encoding unit 414 encodes the binary correction data generated by the correction data generation unit 408 by generic region encoding.
In step 112 (S112), the code generation unit 410 includes code data corresponding to the non-edge information output from the non-edge information encoding unit 412 and edge information (binary correction) output from the edge information encoding unit 414. Code data 900 including code data corresponding to (data) is generated and output.

[Decryption program]
FIG. 10 is a diagram illustrating a functional configuration of the decryption program 5 which is executed by the control device 20 (FIG. 5) and implements the decryption method according to the present invention.
As illustrated in FIG. 10, the decoding program 5 includes a decoding processing unit 500, a non-edge image decoding unit 502, an edge image decoding unit 504, and a decoded image generation unit 506.
Note that all or some of the functions of the decryption program 5 may be realized by an ASIC provided in the printer apparatus 10 or the like.

  In the decoding program 5, the decoding processing unit 500 outputs non-edge information (that is, halftone area code) of the image element to the non-edge image decoding unit 502 based on the input code data 900, and the image element Edge information (that is, generic region code) is output to the edge image decoding unit 504.

Based on the non-edge information of the image element input from the decoding processing unit 500, the non-edge image decoding unit 502 performs non-edge image corresponding to the non-edge portion of the image element (see FIG. 4) by halftone region decoding. The non-edge partial image 614) shown is generated and output to the decoded image generation unit 506.
The edge image decoding unit 504 performs generic region decoding on the basis of the edge information input from the decoding processing unit 500, thereby generating an edge image corresponding to the edge portion of the binary image (binary correction data 620 shown in FIG. 4). ) And output to the decoded image generation unit 506.

  Based on the non-edge image decoded by the non-edge image decoding unit 502 and the edge image decoded by the edge image decoding unit 504, the decoded image generation unit 506 defines a refinement area defined in JBIG2. Is used to generate and output a decoded image 630 (FIG. 4). More specifically, the decoded image generation unit 506 performs a logical sum operation (OR operation) on the non-edge image decoded by the halftone region decoding and the edge image decoded by the generic region decoding. Thus, the decoded image 630 is generated by correcting the non-edge image in the refinement region.

[Decryption operation]
FIG. 11 is a flowchart showing the decryption process (S20) by the decryption program 5.
As shown in FIG. 11, in step 200 (S200), the decoding processing unit 500 (FIG. 10) converts the input code data 900 (FIG. 8) into a halftone area code (identification data for identifying a non-edge portion). And the generic region code (code data of the binary correction data), the halftone region code is output to the non-edge image decoding unit 502, and the generic region code is output to the edge image decoding unit 504. .

In step 202 (S202), the non-edge image decoding unit 502 decodes the non-edge image (non-edge partial image 614) with a halftone dot pattern based on the halftone region code input from the decoding processing unit 500. . The generated non-edge image is input to the decoded image generation unit 506.
In step 204 (S204), the edge image decoding unit 504 decodes the edge image (binary correction data 620) based on the generic region code input from the decoding processing unit 500. The generated edge image is input to the decoded image generation unit 506.

  In step 206 (S206), the decoded image generation unit 506 converts the non-edge image decoded by the non-edge image decoding unit 502 and the edge image decoded by the edge image decoding unit 504 into a refinement region. A logical sum operation is performed to generate and output a decoded image 630 (FIG. 4).

As described above, since the image processing apparatus 2 according to the present embodiment encodes and decodes the edge image and the non-edge image independently, the image processing apparatus 2 can perform the encoding while retaining the fine edge information of the image element. It is possible to improve the reproducibility of fine edges and perform decoding.
Moreover, since the image processing apparatus 2 effectively encodes the image element by halftone area encoding and generic area encoding, it can be encoded at a higher compression rate.

[Second Embodiment]
An image processing apparatus 2 according to a second embodiment of the present invention will be described.
FIG. 12 is a diagram illustrating a functional configuration of the second encoding program 6 that realizes the encoding method according to the present invention.
As illustrated in FIG. 12, the encoding program 6 includes a raster generation unit 400, a multi-value data generation unit 402, a halftone data generation unit 404, an edge detection unit 606, a modified data generation unit 408, and a code generation unit 410. The code generation unit 410 includes a non-edge information encoding unit 412 and an edge information encoding unit 414.
In the encoding program 6, the raster generation unit 400 outputs the acquired input image 602 to the multi-value data generation unit 402, the edge detection unit 606, and the correction data generation unit 408, and the multi-value data generation unit 402 The multi-value image data is output only to the halftone data generator 404, and the edge detector 606 is different from the encoding program 4 (FIG. 6) in that the edge portion of the image element is detected by the density histogram.
Of the components shown in FIG. 12, those substantially the same as those shown in FIG. 6 are denoted by the same reference numerals.

The edge detection unit 606 detects an image portion corresponding to the edge of the input image 602 input from the raster generation unit 400 and outputs the image portion to the correction data generation unit 408. More specifically, the edge detection unit 406 multi-values the input image 602 that has been input and performs edge detection. Multi-value quantization is performed by calculating an average value of pixel values in a peripheral region of the target pixel (for example, a region including the target pixel and eight neighboring pixels of the target pixel) or by calculating a weighted average value. The
Furthermore, the edge detection unit 406 creates a density distribution (histogram) based on the multivalued density values. The edge detection unit 406 detects a predetermined density value or a range of density values as an edge portion of an image element from the created density histogram.

[Encoding operation]
FIG. 13 is a flowchart showing the encoding process (S30) by the encoding program 6. Of the processes shown in FIG. 13, the same reference numerals are given to the processes that are substantially the same as those shown in FIG. 9.
As shown in FIG. 13, in the processing of S100 and S102, a binary input image 602 is input, and a non-edge portion of an image element of the input image 602 is detected. The input image 602 is input to the edge detection unit 606 by the raster generation unit 400.

  In step 300 (S300), the edge detection unit 606 multi-values the input image 602, creates a density histogram based on the multi-value image, and detects an edge portion of the image element. The edge detection unit 606 outputs the position information of the edge portion of the image element to the correction data generation unit 408.

In the processing of S106 to S112, the encoding program 6 generates binary correction data based on the edge portion detected by the edge detection unit 606, encodes the non-edge portion of the image element by halftone region encoding, An edge portion (binary correction data) of an image element is encoded by generic region encoding, and code data is output.
As described above, the image processing apparatus 2 according to the present embodiment creates a density histogram and generates an edge image, so that the edge portion of the image element can be specified and the fine edge information of the image element is retained. Can be encoded.

[Third Embodiment]
An image processing apparatus 2 according to a third embodiment of the present invention will be described.
FIG. 14 is a diagram for explaining edge detection processing by a third encoding program 8 (not shown) that implements the encoding method according to the present invention. The configuration of the encoding program 8 is substantially the same as the configuration of the encoding program 6 (FIG. 12).
As shown in FIG. 14, the edge detection unit 606 calculates a correlation with an edge detection operator (that is, a group of edge patterns prepared in advance) without converting the input image 602 into a multivalued image. Edge part is detected.
The edge detection unit 606 calculates the correlation between the input image 602 illustrated in FIG. 14A and the edge detection operator including various edge patterns prepared in advance illustrated in FIG. Are substantially coincident, it is detected that this image portion is an edge portion.

As shown in FIG. 14C, each of the image portions of the input image 602 is determined by the edge detection unit 606 to be an edge portion or a non-edge portion, and the edge detection result is sent to the correction data generation unit 408. Are output.
Furthermore, as illustrated in FIG. 14D, the correction data generation unit 408 selects an image portion corresponding to the edge from the input image 602, thereby generating binary correction data 620.

[Encoding operation]
FIG. 15 is a flowchart showing the encoding process (S40) by the encoding program 8. Note that among the processes shown in FIG. 15, the same reference numerals are given to the processes that are substantially the same as those shown in FIG. 9.
As shown in FIG. 15, in the processes of S100 and S102, a binary input image 602 is input, and a non-edge portion of an image element of the input image 602 is detected. The input image 602 is input to the edge detection unit 606 by the raster generation unit 400.

  In step 400 (S400), the edge detection unit 606 sequentially calculates the correlation between the input image 602 and the edge detection operator, determines whether the image part is an edge part or a non-edge part, and determines the edge detection result. The data is output to the correction data generation unit 408.

In the processing of S106 to S112, the encoding program 8 generates binary correction data based on the edge portion detected by the edge detection unit 606, encodes the non-edge portion of the image element by halftone region encoding, An edge portion (binary correction data) of an image element is encoded by generic region encoding, and code data is output.
As described above, the image processing apparatus 2 according to the present embodiment generates an edge image using the edge detection operator, so that the edge portion of the image element can be effectively identified and fine edge information of the image element is retained. Can be encoded in the state.

FIG. 1A illustrates a halftone area encoding process. FIG. 1A illustrates a binary image to be encoded, and FIG. 1B is created in the halftone area encoding process. An image dictionary 700 is illustrated, and FIG. 1C illustrates code data generated using the image dictionary 700 and a decoded image 610 thereof. It is a figure which illustrates the image dictionary 702 and the decoded image 612 at the time of encoding the input image 602 in which an edge exists by a halftone area | region encoding process. It is a figure which illustrates the encoding process by the image processing apparatus 2 concerning this invention. It is a figure which illustrates the decoding process by the image processing apparatus 2 concerning this invention. It is a figure which illustrates the hardware constitutions of the image processing apparatus 2 to which the encoding method and decoding method concerning this invention are applied centering on the control apparatus 20. FIG. It is a figure which illustrates the function structure of the 1st encoding program 4 which implement | achieves the encoding method concerning this invention. It is a figure which illustrates the multi-value conversion process by the multi-value data generation part. It is a figure which illustrates the code data produced | generated by the encoding program. It is a flowchart which shows the encoding process (S10) by the encoding program 4. It is a figure which illustrates the function structure of the decoding program 5 which implement | achieves the decoding method concerning this invention. It is a flowchart which shows the decoding process (S20) by the decoding program 5. FIG. It is a figure which illustrates the function structure of the 2nd encoding program 6 which implement | achieves the encoding method concerning this invention. It is a flowchart which shows the encoding process (S30) by the encoding program 6. FIG. It is a figure explaining the edge detection process by the 3rd encoding program 8 which implement | achieves the encoding method concerning this invention. It is a flowchart which shows the encoding process (S40) by the encoding program 8. FIG.

Explanation of symbols

2 ... Image processing device 10 ... Printer device 20 ... Control device 204 ... CPU
204 ... Memory 22 ... Communication device 24 ... Storage device 4 ... Encoding program 400 ... Raster generator 402 ... Multi-value data generator 404 ... Halftone data generator 406 ... Edge detection unit 408 ... Modified data generation unit 410 ... Code generation unit 412 ... Non-edge information encoding unit 414 ... Edge information encoding unit 5 ... Decoding program 500 ... Decoding processing unit 502 ... Non-edge image decoding unit 504 ... Edge image decoding unit 506 ... Decoded image generation unit

Claims (10)

Edge image generation means for generating an edge image corresponding to the edge portion of the input binary image;
Identification data generating means for generating identification data for identifying a non-edge portion of the binary image;
The encoding apparatus which has an encoding means which encodes the edge image produced | generated by the said edge image production | generation means, and the identification data produced | generated by the said identification data production | generation means by a different method. An edge detecting means for detecting an edge of the binary image;
The encoding apparatus according to claim 1, wherein the edge image generation generates an edge image based on an image portion corresponding to the edge detected by the edge detection unit and a binary image. The identification data generating means
Multi-value image generation means for generating a multi-value image having a lower resolution from the input binary image;
The encoding device according to claim 1, further comprising: a halftone dot pattern generation unit that generates a binary halftone dot pattern representing a gradation of the multilevel image generated by the multilevel image generation unit. The encoding unit associates and encodes the halftone dot pattern generated by the halftone dot pattern generation unit and the position in the multilevel image generated by the multilevel image generation unit. Encoding device. Edge image decoding means for decoding an edge image corresponding to the edge portion of the encoded binary image based on the encoded data;
Non-edge image decoding means for decoding a non-edge image corresponding to a non-edge portion of a binary image based on identification data included in the code data;
A decoding apparatus comprising: an image generating unit that generates a binary image based on the edge image decoded by the edge image decoding unit and the non-edge image decoded by the non-edge image decoding unit. . The image generation means performs a logical OR operation on the edge image decoded by the edge image decoding means and the non-edge image decoded by the non-edge image decoding means, thereby obtaining a binary image. The decoding device according to claim 5, which is generated. Generate an edge image corresponding to the edge portion of the input binary image;
Generating identification data identifying non-edge portions of the binary image;
An encoding method that encodes the generated edge image and the generated identification data by different methods. Based on the code data, the edge image corresponding to the edge portion of the encoded binary image is decoded,
Based on the identification data included in the code data, the non-edge image corresponding to the non-edge portion of the binary image is decoded,
A decoding method for generating a binary image based on the decoded edge image and the decoded non-edge image. In an encoding device including a computer,
An edge image generation step for generating an edge image corresponding to an edge portion of the input binary image;
An identification data generating step for generating identification data for identifying a non-edge portion of the binary image;
A program for causing a computer of the encoding apparatus to execute an encoding step of encoding the generated edge image and the generated identification data by different methods. In a decoding device including a computer,
An edge image decoding step for decoding an edge image corresponding to an edge portion of the encoded binary image based on the encoded data;
A non-edge image decoding step of decoding a non-edge image corresponding to a non-edge portion of the binary image based on the identification data included in the code data;
An image generation step for generating a binary image based on the decoded edge image and the decoded non-edge image, and a program to be executed by a computer of the decoding device.

Images