JP4145086B2 - Image decoding apparatus, image processing apparatus, moving image display system, program, storage medium, and image decoding method - Google Patents

Description

[0001]
BACKGROUND OF THE INVENTION
The present invention relates to an image decoding device, an image processing device, a moving image display system, a program, a storage medium, and an image decoding method.
[0002]
[Prior art]
Due to advances in image input technology and output technology, the demand for higher definition of images has increased greatly in recent years. For example, taking a digital camera as an example of an image input device, the price of a high-performance charge coupled device (CCD) having a number of pixels of 3 million or more has progressed, and the spread price range has increased. It has come to be widely used in products. A product with 5 million pixels is also close. And it is said that this increasing trend in the number of pixels will continue for a while.
[0003]
On the other hand, with regard to image output / display devices, for example, products in the hard copy field such as laser printers, ink jet printers, sublimation printers, and flats such as CRTs, LCDs (liquid crystal display devices), and PDPs (plasma display devices). The high definition and low price of products in the soft copy field of panel displays are remarkable.
[0004]
Due to the market launch of these high-performance, low-priced image input / output products, high-definition images have become popular, and it is expected that demand for high-definition images will increase in all situations. In fact, the development of technologies related to networks such as personal computers and the Internet is accelerating these trends. In particular, recently, mobile devices such as mobile phones and notebook personal computers have become very popular, and opportunities for transmitting or receiving high-definition images from any point using communication means are rapidly increasing.
[0005]
Against this background, it is inevitable that the demand for higher performance or higher functionality for image compression / decompression technology that facilitates the handling of high-definition images will become stronger in the future.
[0006]
Thus, in recent years, a new method called JPEG2000, which can restore high-quality images even at a high compression rate, is being standardized as one of image compression methods that satisfy these requirements. In JPEG2000, it is possible to perform compression / decompression processing in a small memory environment by dividing an image into rectangular regions (tiles). That is, each tile becomes a basic unit for executing the compression / decompression process, and the compression / decompression operation can be performed independently for each tile.
[0007]
[Problems to be solved by the invention]
By the way, the division processing in JPEG2000 is called tiling, and it is an effective technique for saving memory and speeding up. However, "JX Wei, MR Pickering, MR Frater and JF Arnold," Block-Based Wavelet Image Compression, "in VCIP 2000, KN Ngan, T. Sikora, MT Sun Eds., Proc. Of SPIE Vol. 4067, pp. 1290-1295, 20-23 June 2000, Perth, Australia" As described, when the compression / decompression process is performed under a condition with a high compression rate, there is a problem in that the tile boundary becomes discontinuous in the expanded image.
[0008]
Therefore, in order to solve such a problem, a technique for making the tile boundary inconspicuous by applying a uniform low-pass filter only in the vicinity of the tile boundary has been proposed.
[0009]
Further, such a JPEG 2000 image of one frame can be converted into a moving image by being continuously displayed at a predetermined frame rate (the number of frames reproduced per unit time).
[0010]
However, since the processing using the low-pass filter as described above requires a relatively large amount of calculation, it takes time for the filtering processing, and as a result, a delay in the reproduction processing may be caused. In particular, a delay in reproduction processing in a moving image causes problems such as deviation from sound and frame dropping.
[0011]
The object of the present invention is to achieve a balance between the decoding processing speed and the image quality by smoothing the distortion at the tile boundary, thereby eliminating adverse effects such as frame dropping without the decoding process catching up with the reproduction, and the distortion at the tile boundary. Image decoding apparatus, image processing apparatus, moving image display system, program, storage medium, and image decoding method.
[0012]
[Means for Solving the Problems]
  An image decoding apparatus according to the present invention is an image decoding apparatus that continuously decodes a plurality of frames in which pixel values are discrete wavelet transformed and compression-coded for each tile obtained by dividing an image into a plurality of tiles.
  A tile boundary smoothing unit that performs a first tile boundary smoothing process or a second tile boundary smoothing process for smoothing distortion of a tile boundary in each frame after decoding, and a tile by the tile boundary smoothing unit Mode selection means for selecting an image quality priority mode that prioritizes image quality or a speed priority mode that prioritizes processing speed for boundary distortion smoothing processing, and smoothing of tile boundary distortion in each frame after decoding by the tile boundary smoothing means For processing, according to the selection by the mode selection means,speedWhen the priority mode is selected, switch to the first tile boundary smoothing process,image qualityAnd tile boundary smoothing switching means for switching to the second tile boundary smoothing process when the priority mode is selected, wherein the first tile boundary smoothing process is a tile in the decoded frame. A uniform low-pass filter is applied to pixels in the vicinity of the boundary, and the second tile boundary smoothing processing is performed on the pixels in the vicinity of the tile boundary in the decoded frame with respect to the inter-pixel distance from the tile boundary of the pixel. Edge amount in the diagonal direction of pixels near the tile boundaryThe greater the value, the smaller the smoothnessA controlled low-pass filter is applied.
[0013]
  Therefore, the image quality priority mode and the speed priority mode are switched according to the selection by the mode selection means, and the tile boundary distortion smoothing process in each frame after decoding by the tile boundary smoothing means is executed. As a result, it is possible to appropriately select the image quality priority mode that prioritizes the image quality and the speed priority mode that prioritizes the processing speed and execute the tile boundary distortion smoothing process.Become possible.
[0032]
  Of the present inventionImage processing deviceButDivide into multipleWasPixel value for each tileButDiscrete wavelet transformCompression encodingConsecutively decoded multiple framesAny one of the image decoding apparatuses of the present inventionAnd an image display device that displays on the display device an image based on the frame decoded by the image decoding device.
[0033]
  Therefore,Image decoding apparatus of the present inventionIt is possible to provide an image processing apparatus that exhibits the same effect as the above.
[0034]
  Of the present inventionThe moving image display system includes an image input device that captures a moving image,AboveCaptured by image input deviceWasVideoTheMultiple per frameofDivided into tilesThe aboveDiscrete wavelet transform of pixel values for each tileCompression codingAn image compression device,AboveDecodes multiple frames compression-encoded by image compression deviceAny one of the image decoding apparatuses of the present inventionWhen,AboveAn image display device that displays on the display device an image based on the frame decoded by the image decoding device.
[0035]
  Therefore,Image decoding apparatus of the present inventionIt is possible to provide a moving image display system having the same effect as the above.
[0036]
  The program of the present invention causes a computer to execute any one of the image decoding methods of the present invention..
[0037]
  Therefore,It is possible to provide a program having the same operation as the image decoding method of the present invention..
[0056]
  The present inventionStorage mediaOf the present inventionprogramAny one or more ofIs remembered.
[0057]
  Therefore, by having the computer read the program stored in this storage medium,Image decoding method of the present inventionIt is possible to obtain the same effect as.
[0058]
  The image decoding method of the present invention is an image decoding method for continuously decoding a plurality of frames in which pixel values are subjected to discrete wavelet transform and compression-coded for each tile obtained by dividing an image into a plurality of tiles.
  A tile boundary smoothing step for performing a first tile boundary smoothing process or a second tile boundary smoothing process for smoothing distortion of a tile boundary in each frame after decoding, and a tile in the tile boundary smoothing process A mode selection step of selecting an image quality priority mode that prioritizes image quality or a speed priority mode that prioritizes processing speed for boundary distortion smoothing processing, and smoothing of tile boundary distortion in each frame after decoding by the tile boundary smoothing step For processing, according to the selection by the mode selection step,speedWhen the priority mode is selected, switch to the first tile boundary smoothing process,image qualityA tile boundary smoothing switching step for switching to the second tile boundary smoothing process when the priority mode is selected, and the first tile boundary smoothing process includes a tile in a frame after decoding; A uniform low-pass filter is applied to pixels in the vicinity of the boundary, and the second tile boundary smoothing processing is performed on the pixels in the vicinity of the tile boundary in the decoded frame with respect to the inter-pixel distance from the tile boundary of the pixel. Edge amount in the diagonal direction of pixels near the tile boundaryThe greater the value, the smaller the smoothnessA controlled low-pass filter is applied.
[0059]
  Therefore, the image quality priority mode and the speed priority mode are switched according to the selection in the mode selection step, and the tile boundary distortion smoothing process in each frame after decoding in the tile boundary smoothing step is executed. As a result, it is possible to appropriately select the image quality priority mode that prioritizes the image quality and the speed priority mode that prioritizes the processing speed and execute the tile boundary distortion smoothing process.Become possible.
[0078]
DETAILED DESCRIPTION OF THE INVENTION
First, an outline of the “hierarchical encoding algorithm” and the “JPEG2000 algorithm” that are the premise of the present embodiment will be described.
[0079]
FIG. 1 is a functional block diagram of a system that implements a hierarchical encoding algorithm that is the basis of the JPEG2000 system. This system includes color space transform / inverse transform unit 101, two-dimensional wavelet transform / inverse transform unit 102, quantization / inverse quantization unit 103, entropy encoding / decoding unit 104, and tag processing unit 105. It is configured.
[0080]
One of the biggest differences between this system and the conventional JPEG algorithm is the conversion method. In JPEG, discrete cosine transform (DCT) is used. In this hierarchical coding algorithm, the two-dimensional wavelet transform / inverse transform unit 102 uses discrete wavelet transform (DWT). ing. DWT has the advantage of better image quality in the high compression region than DCT, and this is one of the main reasons why DWT is adopted in JPEG2000, which is a successor algorithm of JPEG.
[0081]
Another major difference is that in this hierarchical encoding algorithm, a functional block of the tag processing unit 105 is added in order to perform code formation at the final stage of the system. The tag processing unit 105 generates compressed data as code string data during an image compression operation, and interprets code string data necessary for decompression during the decompression operation. And JPEG2000 can realize various convenient functions by code string data. For example, the compression / decompression operation of a still image can be freely stopped at an arbitrary layer (decomposition level) corresponding to octave division in block-based DWT (see FIG. 3 described later).
[0082]
In many cases, color space conversion / inverse conversion 101 is connected to the input / output portion of the original image. For example, the RGB color system composed of R (red) / G (green) / B (blue) components of the primary color system and the Y (yellow) / M (magenta) / C (cyan) components of the complementary color system This corresponds to the part that performs conversion or reverse conversion from the YMC color system consisting of the above to the YUV or YCbCr color system.
[0083]
Next, the JPEG2000 algorithm will be described.
[0084]
As shown in FIG. 2, in a color image, each component 111 (RGB primary color system here) of an original image is generally divided by a rectangular area. This divided rectangular area is generally called a block or a tile. In JPEG2000, it is generally called a tile. Therefore, such a divided rectangular area is hereinafter referred to as a tile. (In the example of FIG. 2, each component 111 is divided into a total of 16 rectangular tiles 112, 4 × 4 in length and breadth). When such individual tiles 112 (R00, R01,..., R15 / G00, G01,..., G15 / B00, B01,..., B15 in the example of FIG. 2) execute the image data compression / decompression process. It becomes the basic unit. Therefore, the compression / decompression operation of the image data is performed independently for each component and for each tile 112.
[0085]
At the time of encoding image data, the data of each tile 112 of each component 111 is input to the color space conversion / inverse conversion unit 101 in FIG. A dimensional wavelet transform (forward transform) is applied to divide the space into frequency bands.
[0086]
FIG. 3 shows subbands at each decomposition level when the number of decomposition levels is three. In other words, the tile original image (0LL) (decomposition level 0) obtained by tile division of the original image is subjected to two-dimensional wavelet transform, and the subbands (1LL, 1HL, 1LH shown in the decomposition level 1) , 1HH). Subsequently, the low-frequency component 1LL in this hierarchy is subjected to two-dimensional wavelet transformation to separate the subbands (2LL, 2HL, 2LH, 2HH) indicated by the decomposition level 2. Similarly, the low-frequency component 2LL is also subjected to two-dimensional wavelet transform to separate subbands (3LL, 3HL, 3LH, 3HH) shown in the decomposition level 3. In FIG. 3, the subbands to be encoded at each decomposition level are indicated by shading. For example, when the number of decomposition levels is 3, subbands (3HL, 3LH, 3HH, 2HL, 2LH, 2HH, 1HL, 1LH, 1HH) indicated by shading are to be encoded, and the 3LL subband is encoded. It is not converted.
[0087]
Next, the bits to be encoded are determined in the specified encoding order, and the context is generated from the bits around the target bits by the quantization / inverse quantization unit 103 shown in FIG.
[0088]
The wavelet coefficients that have undergone the quantization process are divided into non-overlapping rectangles called “precincts” for each subband. This was introduced to use memory efficiently in implementation. As shown in FIG. 4, one precinct consists of three rectangular regions that are spatially coincident. Further, each precinct is divided into non-overlapping rectangular “code blocks”. This is the basic unit for entropy coding.
[0089]
The coefficient values after wavelet transform can be quantized and encoded as they are, but in JPEG2000, in order to increase the encoding efficiency, the coefficient values are decomposed into “bit plane” units, and each pixel or code block is divided. Ranking can be performed on “bitplanes”.
[0090]
Here, FIG. 5 is an explanatory diagram showing an example of a procedure for ranking the bit planes. As shown in FIG. 5, this example is a case where the original image (32 × 32 pixels) is divided into four 16 × 16 pixel tiles, and the size of the precinct and code block at the composition level 1 is Each is 8 × 8 pixels and 4 × 4 pixels. The numbers of the precinct and the code block are assigned in raster order. In this example, the number of assigns is assigned from numbers 0 to 3, and the code block is assigned from numbers 0 to 3. A mirroring method is used for pixel expansion outside the tile boundary, wavelet transform is performed with a reversible (5, 3) filter, and a wavelet coefficient value of decomposition level 1 is obtained.
[0091]
An explanatory diagram showing an example of the concept of a typical “layer” configuration for tile 0 / precinct 3 / code block 3 is also shown in FIG. The converted code block is divided into subbands (1LL, 1HL, 1LH, 1HH), and wavelet coefficient values are assigned to the subbands.
[0092]
The layer structure is easy to understand when the wavelet coefficient values are viewed from the horizontal direction (bit plane direction). One layer is composed of an arbitrary number of bit planes. In this example, layers 0, 1, 2, and 3 are made up of bit planes of 1, 3, 1, and 3, respectively. A layer including a bit plane close to LSB (Least Significant Bit) is subject to quantization first. Conversely, a layer close to MSB (Most Significant Bit) is quantized to the end. It will remain without being. A method of discarding from a layer close to the LSB is called truncation, and the quantization rate can be finely controlled.
[0093]
The entropy encoding / decoding unit 104 illustrated in FIG. 1 performs encoding on the tile 112 of each component 111 by probability estimation from the context and the target bit. In this way, encoding processing is performed in units of tiles 112 for all components 111 of the original image. Finally, the tag processing unit 105 performs a process of combining all the encoded data from the entropy encoding / decoding unit 104 into one code string data and adding a tag thereto.
[0094]
FIG. 6 shows a schematic configuration for one frame of the code string data. The header of this code string data and the head of the code data (bit stream) of each tile (main header, tile part header (tile part header which is tile boundary position information, tile boundary direction information, etc.)) Is added, followed by encoded data for each tile. In the main header, coding parameters and quantization parameters are described. A tag (end of codestream) is placed again at the end of the code string data.
[0095]
On the other hand, when the encoded data is decoded, the image data is generated from the code string data of each tile 112 of each component 111, contrary to the case of encoding the image data. In this case, the tag processing unit 105 interprets tag information added to the code string data input from the outside, decomposes the code string data into code string data of each tile 112 of each component 111, and Decoding processing (decompression processing) is performed for each code string data of each tile 112. At this time, the position of the bit to be decoded is determined in the order based on the tag information in the code string data, and the quantization / inverse quantization unit 103 determines the peripheral bits (that have already been decoded) of the target bit position. Context is generated from the sequence of The entropy encoding / decoding unit 104 performs decoding by probability estimation from the context and code string data, generates a target bit, and writes it in the position of the target bit. Since the data decoded in this way is spatially divided for each frequency band, the two-dimensional wavelet transform / inverse transform unit 102 performs two-dimensional wavelet inverse transform on each of the components of the image data. The tile is restored. The restored data is converted to original color system image data by the color space conversion / inverse conversion unit 101.
[0096]
The above is the outline of the “JPEG2000 algorithm”, and the “Motion JPEG2000 algorithm” is an extension of a still image, that is, a method for a single frame to a plurality of frames. That is, “Motion JPEG2000”, as shown in FIG. 7, is a moving image by continuously displaying a JPEG2000 image of one frame at a predetermined frame rate (the number of frames reproduced per unit time). .
[0097]
Hereinafter, a first embodiment of the present invention will be described. Here, an example relating to a moving image compression / decompression technique typified by Motion JPEG2000 will be described. Needless to say, the present invention is not limited to the contents of the following description.
[0098]
FIG. 8 is a system configuration diagram showing the surveillance camera system 1 to which the present invention is applied, and FIG. 9 is a functional block diagram thereof. As shown in FIG. 8, a surveillance camera system 1 to which the moving image display system of the present invention is applied includes a surveillance camera 1a that functions as an image recording device and a personal computer (hereinafter referred to as PC) 1b that functions as an image processing device. Are connected via a network 1c which is the Internet.
[0099]
As shown in FIG. 9, the monitoring camera 1a of such a monitoring camera system 1 includes an image input device 2 that captures a moving image using a photoelectric conversion device such as a CCD or MOS image sensor, and the captured image data. And an image compression apparatus 3 that performs compression encoding. On the other hand, the PC 1b decompresses (decodes) the code string data generated by the image compression device 3 of the surveillance camera 1a to generate image data of a moving image, and the decompressed image. An image display device 7 that displays an image based on data, and a code string storage unit 9 that stores code string data generated by the image compression device 3 of the surveillance camera 1a are provided. The code string storage unit 9 functions as a general buffer, or functions as a storage of code string data of moving images over a long period of time, and is used depending on the application.
[0100]
FIG. 10 is a block diagram illustrating an example of a hardware configuration of the surveillance camera system 1. As shown in FIG. 10, the surveillance camera 1a and the PC 1b constituting the surveillance camera system 1 are respectively provided with CPUs (Central Processing Units) 11a and 11b that are main parts of the computer and control each part centrally. The CPUs 11a and 11b include memories 12a and 12b that are storage media including various ROMs (Read Only Memory) and RAMs (Random Access Memory), predetermined communication interfaces 13a and 13b that communicate with the network 1c, and a user. The operation panels 18a and 18b for receiving various operations are connected via buses 14a and 14b.
[0101]
As described above, the monitoring camera 1a includes the image input device 2 and the image compression device 3, and the image input device 2 and the image compression device 3 are also connected to the CPU 11a via the bus 14a.
[0102]
The PC 1b includes an image display device 7, a display 19 that is a display device such as a CRT (Cathode Ray Tube) or LCD (Liquid Crystal Display), and an HDD (Hard Disk Drive) that is an external storage device that functions as the code string storage unit 9. ) 15 and a drive 17 that is a mechanism for reading the computer software from the storage medium 16 that stores the computer software that is a distributed program (for example, a moving image processing program), and these image display devices 7 The display 19, the HDD 15, and the drive 17 are also connected to the CPU 11b via the bus 14b.
[0103]
Control programs such as a moving image processing program for processing moving images are stored in the memory 12b (of the ROM) of the PC 1b having such a configuration. This moving image processing program implements the program of the present invention. Then, the function of the image expansion device 6 is realized by processing executed by the CPU 11b based on this moving image processing program.
[0104]
As the storage medium 16, various types of media such as various optical disks such as CD and DVD, various magnetic disks such as various magneto-optical disks and flexible disks, and semiconductor memories can be used. Alternatively, the program may be downloaded from the network 1c and installed in the memory 12b. In this case, the storage device storing the program in the server on the transmission side is also a storage medium of the present invention. Note that the program may operate on a predetermined OS (Operating System), and in that case, the OS may take over the execution of some of the various processes described later, It may be included as a part of a group of program files constituting the application software or OS.
[0105]
Here, the operation of each part of the surveillance camera system 1 will be briefly described. First, the image input device 2 of the surveillance camera 1a captures a moving image in units of frames using a photoelectric conversion device such as a CCD or a MOS image sensor, and outputs a digital pixel value signal of the moving image to the image compression device 3. The image compression apparatus 3 compresses and encodes the digital pixel value signal of the moving image according to the “Motion JPEG2000 algorithm”. By the processing in the image compression device 3, the moving image data of the R, G, and B components of the original moving image is divided into one or a plurality of (usually a plurality of) tiles for each frame, and each tile is layered. Thus, the encoded data is compressed and encoded. The code string data (Motion JPEG2000 data) generated according to the “Motion JPEG2000 algorithm” in this way is output to the PC 1b via the network 1c.
[0106]
The code string data (Motion JPEG2000 data) output to the PC 1b via the network 1c is stored in the code string storage unit 9 in the PC 1b, and is expanded by the image expansion device 6. Then, the image data of the moving image generated by the decompression process by the image decompression device 6 is output to the image display device 7, and an image based on the decompressed image data is displayed on the display 19.
[0107]
Next, the image expansion device 6 that is a main part of the present invention will be described in detail. Here, FIG. 11 is a functional block diagram of the image expansion device 6. As shown in FIG. 11, the CPU 11b operates based on computer software, so that the image decompression device 6 has a mode selection unit 20, a tag processing unit 21, an entropy decoding unit 22, an inverse quantization unit 23, and a two-dimensional wavelet. The functions of the inverse transformation unit 24, the color space inverse transformation unit 25, the tile boundary smoothing switching unit 26, the first tile boundary smoothing unit 27, and the second tile boundary smoothing unit 28 are realized. Note that the functions realized by the tag processing means 21, entropy decoding means 22, inverse quantization means 23, two-dimensional wavelet inverse transform means 24, and color space inverse transform means 25 are the spatial transform / inverse shown in FIG. Since the description has been given for the transform unit 101, the two-dimensional wavelet transform / inverse transform unit 102, the quantization / inverse quantization unit 103, the entropy encoding / decoding unit 104, and the tag processing unit 105, description thereof is omitted here.
[0108]
The mode selection means 20 exhibits a function for designating a processing mode. Specifically, the mode selection means 20 displays a mode designation screen X as shown in FIG. The mode designation screen X is provided with a radio button B for selecting either the speed priority mode or the image quality priority mode. Then, after the operator operates the operation panel 18b to designate one radio button B, the operator operates the OK button A to designate the processing mode. When the processing mode is designated in this way, a signal indicating the designated processing mode is output to the tile boundary smoothing switching means 26.
[0109]
The tile boundary smoothing switching unit 26 exhibits a function of determining whether the first tile boundary smoothing unit 27 or the second tile boundary smoothing unit 28 performs the smoothing process in the vicinity of the tile boundary. The tile boundary smoothing switching unit 26 receives the RGB data obtained by the color space inverse conversion unit 25 and the signal indicating the processing mode output from the mode selection unit 20.
[0110]
If the tile boundary smoothing switching unit 26 determines that the speed priority mode has been selected, the tile boundary smoothing switching unit 26 outputs the RGB data obtained by the color space inverse conversion unit 25 to the first tile boundary smoothing unit 27. If it is determined that the image quality priority mode is selected, the RGB data obtained by the color space inverse transform unit 25 is output to the second tile boundary smoothing unit 28.
[0111]
The first tile boundary smoothing means 27 and the second tile boundary smoothing means 28 smooth the pixels in the vicinity of the tile boundary with respect to the RGB data obtained by the color space inverse conversion means 25, thereby conspicuous the distortion of the tile boundary. It is something to lose. FIG. 13 is an explanatory diagram showing an example of processing in the first tile boundary smoothing means 27 and the second tile boundary smoothing means 28. As shown in FIG. 13, the first tile boundary smoothing means 27 and the second tile boundary smoothing means 28 apply to pixels in the vicinity of the tile boundary (pixels in the shaded area including the tile boundary pixels in FIG. 13). Apply a low pass filter.
[0112]
First, a specific example of processing in the first tile boundary smoothing means 27 will be shown. Here, FIG. 14 is an explanatory diagram illustrating an example of a low-pass filter at a vertical tile boundary. As shown in FIG. 14, a vertical tile boundary a (see FIG. 13) is subjected to a low-pass filter (one-dimensional horizontally long filter) F1 perpendicular to the vertical tile boundary a, so that the vertical tile boundary a Boundary distortion can be suppressed. In this embodiment, an example of a one-dimensional horizontally long filter has been described. However, any filter may be used as long as it has a frequency characteristic that reduces frequency components in the horizontal direction.
[0113]
FIG. 15 is an explanatory diagram illustrating an example of a low-pass filter at a horizontal tile boundary. As shown in FIG. 15, the horizontal tile boundary b (see FIG. 13) is subjected to a low-pass filter (one-dimensional vertical filter) F2 perpendicular to the horizontal tile boundary b, whereby a horizontal tile boundary b is applied. Boundary distortion can be suppressed. In the present embodiment, an example of a one-dimensional vertically long filter has been described. However, any filter may be used as long as the low-pass filter has a frequency characteristic that reduces frequency components in the vertical direction.
[0114]
FIG. 16 is an explanatory diagram showing an example of a low-pass filter in the vicinity of the intersection between the vertical tile boundary and the horizontal tile boundary. As shown in FIG. 16, by applying a cross-shaped low-pass filter F3 to the vicinity of the intersection between the vertical tile boundary a and the horizontal tile boundary b, the vertical tile boundary a and the horizontal tile boundary b are applied. Tile boundary distortion near the intersection with can be suppressed. In the present embodiment, an example of a cross-shaped filter has been described. However, any filter may be used as long as it has a frequency characteristic that reduces both the vertical and horizontal frequency components.
[0115]
Next, a specific example of processing in the second tile boundary smoothing means 28 will be shown. Here, FIG. 17 is an explanatory diagram showing an example of a low-pass filter at a vertical tile boundary. As shown in FIG. 16, a vertical tile boundary a (see FIG. 13) is subjected to a low-pass filter (one-dimensional horizontally long filter) F4 perpendicular to the vertical tile boundary a, whereby the vertical tile boundary a. Boundary distortion can be suppressed. In this embodiment, an example of a one-dimensional horizontally long filter has been described. However, any filter may be used as long as it has a frequency characteristic that reduces frequency components in the horizontal direction.
[0116]
FIG. 18 is an explanatory diagram showing an example of a low-pass filter at a horizontal tile boundary. As shown in FIG. 18, the horizontal tile boundary b (see FIG. 13) is subjected to a low-pass filter (one-dimensional vertical filter) F5 perpendicular to the horizontal tile boundary b to thereby apply a horizontal tile. Boundary distortion can be suppressed. In the present embodiment, an example of a one-dimensional vertically long filter has been described. However, any filter may be used as long as the low-pass filter has a frequency characteristic that reduces frequency components in the vertical direction.
[0117]
FIG. 19 is an explanatory diagram showing an example of a low-pass filter in the vicinity of the intersection between the vertical tile boundary and the horizontal tile boundary. As shown in FIG. 19, by applying a cross-shaped low-pass filter F6 to the vicinity of the intersection of the vertical tile boundary a and the horizontal tile boundary b, the vertical tile boundary a and the horizontal tile boundary b are applied. Tile boundary distortion near the intersection with can be suppressed. In the present embodiment, an example of a cross-shaped filter has been described. However, any filter may be used as long as it has a frequency characteristic that reduces both the vertical and horizontal frequency components.
[0118]
By the way, the weighting coefficient m at the filter center of the low-pass filters F4, F5, and F6 is variably controlled according to the inter-pixel distance from the tile boundary and the edge amount of the pixels near the tile boundary. That is, the second tile boundary smoothing means 28 is configured to switch the strength of the low-pass filters F4, F5, and F6 according to the inter-pixel distance from the tile boundary and the edge amount of the pixels near the tile boundary.
[0119]
First, a method for calculating the inter-pixel distance from the tile boundary will be described. FIG. 20 is an explanatory diagram illustrating an example of a method for calculating the inter-pixel distance from the tile boundary. As shown in FIG. 20, in each pixel, the distance from the tile boundary from the top, bottom, left, and right is calculated. Those minimum values are set as the distance from the tile boundary in each pixel.
[0120]
Next, a method for calculating the edge amount of pixels near the tile boundary will be described. Here, FIG. 21 is an explanatory diagram showing an example of an edge amount calculation filter. The edge amount of the pixel near the tile boundary is calculated using the edge amount calculation filter shown in FIG. 21 for the pixel near the tile boundary. This edge amount calculation filter calculates an edge amount in an oblique direction. This is for avoiding the conspicuous tile boundary because the edge amount becomes large at the boundary portion of the tile boundary when extracting the edge amount in the vertical and horizontal directions. Note that the direction of the tile boundary is acquired from information included in the encoded data.
[0121]
That is, when the inter-pixel distance from the tile boundary is d and the edge amount of the pixel near the tile boundary is E, the weighting coefficient m at the filter center of the low-pass filter is any of the following formulas (1) to (3). The calculation is performed for each case.
[0122]
When “d = 0 and abs (E) ≧ 255”
m = 4 + abs (E) (1)
When “d = 0 and abs (E) <255”
m = 4 (2)
When “d> 0”
m = max (4 + 64 * d, 4 + abs (E)) (3)
This means that the smoothing degree of the low-pass filter to be applied is reduced as the distance between pixels from the tile boundary is larger and as the absolute value of the edge amount of the pixel near the tile boundary is larger. The reason why the control is performed independently only in the case of “d = 0” is that the tile boundary becomes conspicuous unless the low-pass filter having a certain degree of smoothness is applied to the nearest pixel of the tile boundary.
[0123]
As a result, in the case of the second tile boundary smoothing means 28 in the image quality priority mode, the strength of the low pass filter is adaptively controlled. Therefore, the first tile in the speed priority mode in which a uniform low pass filter is applied to the pixels. Compared with the boundary smoothing means 27, it is possible to reproduce an image with good quality.
[0124]
Further, the second tile boundary smoothing means 28 in the image quality priority mode adaptively controls the strength of the low-pass filter according to the inter-pixel distance from the tile boundary and the edge amount of the pixels near the tile boundary. While suppressing the boundary distortion, it is possible to suppress the image quality degradation that occurs when the edge is strong near the tile boundary.
[0125]
Here, it is possible to appropriately select the image quality priority mode that prioritizes image quality and the speed priority mode that prioritizes processing speed and execute the tile boundary distortion smoothing process, so the decoding processing speed and tile boundary distortion smoothing can be performed. By achieving a balance with the image quality by the conversion, it is possible to suppress the distortion of the tile boundary while eliminating an adverse effect such as the frame dropping without the decoding process catching up with the reproduction.
[0126]
In this embodiment, the image compression / decompression method according to the “JPEG2000 algorithm” has been described. However, the present invention is not limited to this, and any image compression / decompression method in which the compression code includes tile boundary position information may be used. Any image compression / decompression method may be used.
[0127]
Next, a second embodiment of the present invention will be described. Note that the same parts as those described in the first embodiment are denoted by the same reference numerals, and description thereof is omitted (the same applies to the following embodiments).
[0128]
FIG. 22 is a functional block diagram of the image decompression apparatus 6 of the present embodiment. As shown in FIG. 22, the present embodiment includes a mode selection means 30 instead of the mode selection means 20 of the first embodiment.
[0129]
The mode selection unit 30 is the same as the mode selection unit 20 in that it exhibits a function of specifying a processing mode. Specifically, the mode selection unit 30 selects either the speed priority mode or the image quality priority mode for each frame according to the type of frame. For example, as shown in FIG. 23, the image quality priority mode is designated only in the case of “start frame” at time t0, “final frame” at time tn, and “stop frame” at time tk. This is because the tile boundary is not conspicuous during moving image reproduction, and only the “start frame”, “final frame”, and “stop frame” in which tile boundary distortion is conspicuous is subjected to smoothing processing with priority on image quality. When the processing mode is designated in this way, a signal indicating the designated processing mode is output to the tile boundary smoothing switching means 26.
[0130]
Here, since the tile boundary distortion is more conspicuous in the still image than in the moving image, by selecting the image quality priority mode for the start frame of the moving image, the final frame, and the stop frame related to the stop of the reproduction of the moving image, it can be performed at high speed. In addition, the distortion of the tile boundary can be suppressed with high accuracy.
[0131]
Next, a third embodiment of the present invention will be described. FIG. 24 is a functional block diagram of the image decompression apparatus 6 of this embodiment. As shown in FIG. 24, the present embodiment includes a mode selection means 40 instead of the mode selection means 20 of the first embodiment.
[0132]
The mode selection means 40 is the same as the mode selection means 20 in that it exhibits the function of specifying the processing mode. Specifically, the mode selection means 40 selects either the speed priority mode or the image quality priority mode according to the frame rate (the number of frames played back per unit time). That is, when the frame rate is larger than the predetermined threshold, the speed priority mode is selected, and the image quality priority mode is selected otherwise. For example,
Frame rate is higher than “5” → Speed priority mode
Frame rate is "5" or lower → Image quality priority mode
Control like this. This is because the higher the frame rate, the higher the reproduction speed and the less likely the tile boundary distortion is noticeable. When the processing mode is designated in this way, a signal indicating the designated processing mode is output to the tile boundary smoothing switching means 26.
[0133]
Here, since the tile boundary distortion becomes less conspicuous as the frame rate increases in the moving image, the speed priority mode is selected when the frame rate is larger than the predetermined threshold, and when the frame rate is smaller than the predetermined threshold. By selecting the image quality priority mode, it is possible to suppress the distortion of the tile boundary while eliminating an adverse effect such as frame dropping without the decoding process catching up with reproduction.
[0134]
Next, a fourth embodiment of the present invention will be described. FIG. 25 is a functional block diagram of the image decompression apparatus 6 according to this embodiment. As shown in FIG. 25, the present embodiment includes a mode selection means 50 in place of the mode selection means 20 of the first embodiment.
[0135]
The mode selection means 50 is the same as the mode selection means 20 in that it exhibits the function of specifying the processing mode. Specifically, the mode selection means 50 selects either the speed priority mode or the image quality priority mode for each frame in accordance with the code amount to be decoded for each frame.
[0136]
In JPEG2000, in order to set the code amount (compression rate) of a moving image to a predetermined value, the code amount is different for each frame. For example, a frame having a high information amount has a large code amount, and a frame having a small amount of image quality deterioration such as after a scene change has a small code amount. In JPEG2000, it is possible to decode a predetermined part of a code instead of decoding all codes at the time of decompression.
[0137]
In general, if the amount of code to be decoded is small, the compression rate in the frame increases, and tile boundary distortion tends to be conspicuous. Conversely, if the amount of code to be decoded is large, the compression rate in the frame is small, and tile boundary distortion is not noticeable.
[0138]
Therefore, as shown in FIG. 26, the speed priority mode is selected when the amount of codes to be decoded is larger than a predetermined threshold, and the image quality priority mode is selected otherwise.
[0139]
Here, select the image quality priority mode because the frame boundary distortion is conspicuous because the compression rate is large for frames with a small code amount, and the speed priority mode is selected because the frame boundary distortion is inconspicuous because the compression rate is small for frames with a large code amount. By selecting, the optimum tile boundary distortion smoothing process is executed for all frames, so that a high-quality reproduced image can be obtained.
[0140]
Next, a fifth embodiment of the present invention will be described. This embodiment is different from the first embodiment in the function of the image expansion device 6. In general, instead of applying a low-pass filter to all pixels near the tile boundary, the tile boundary to which the low-pass filter is applied is limited, and only the pixels near the tile boundary are subjected to the low-pass filter. .
[0141]
FIG. 27 is a functional block diagram of the image decompression apparatus 6 of the present embodiment. As shown in FIG. 27, the CPU 11b operates based on computer software (image processing program), so that the image decompression device 6 includes a tag processing unit 21, an entropy decoding unit 22, an inverse quantization unit 23, and a two-dimensional wavelet. The functions of the inverse transform unit 24, the color space inverse transform unit 25, the tile boundary smoothing switching unit 26, the first tile boundary smoothing unit 27, the second tile boundary smoothing unit 28, and the correction tile boundary limiting unit 29 are realized. .
[0142]
The corrected tile boundary limiting unit 29 has a function of limiting the tile boundary to be subjected to the low pass filter in the first tile boundary smoothing unit 27 and the second tile boundary smoothing unit 28.
[0143]
Here, FIG. 28 and FIG. 29 are explanatory diagrams illustrating an example of a process for applying a low-pass filter only to a tile boundary in a region of interest (ROI) region. This ROI region is a part of the entire image when it is cut out and enlarged from the entire image or emphasized as compared with other parts.
[0144]
FIG. 28 shows a case where the ROI region is a region along the tile boundary. When the ROI boundary is set as shown in FIG. 28 (a), the tile boundary to which the low-pass filter is applied is set in the portion indicated by the dotted line in FIG. 28 (b). A low-pass filter is not applied to the ROI boundary indicated by the bold line in FIG.
[0145]
FIG. 29 shows a case where the ROI region is a region not along the tile boundary. When the ROI boundary is set as shown in FIG. 29 (a), the tile boundary to which the low-pass filter is applied is set in the portion indicated by the dotted line in FIG. 29 (b). Whether the tile boundary pixel is inside the ROI is calculated by calculation. If the tile boundary pixel is inside the ROI, a low pass filter is applied to the pixel. If the tile boundary pixel is outside the ROI, no low pass filter is applied to the pixel.
[0146]
In the present embodiment, whether or not to apply the low pass filter is determined depending on whether or not it is inside the ROI, but other than that, the low pass filter is applied only to the tile boundary pixels of the portion where the edge amount of the vertical or horizontal component is large. You may perform control to apply.
[0147]
As a result, the corrected tile boundary limiting unit 29 limits the tile boundary pixels to be subjected to the low-pass filter, and performs the color space inverse conversion unit 25 with respect to the first tile boundary smoothing unit 27 and the second tile boundary smoothing unit 28. RGB data obtained by the above is output.
[0148]
Here, by controlling the tile boundary pixels to be subjected to the low-pass filter, the processing time for suppressing the tile boundary distortion can be shortened. In particular, the processing time for suppressing tile boundary distortion can be shortened by applying a low pass filter only to the tile boundary in the ROI region.
[0149]
In each of the embodiments, the PC 1b is applied as a moving image playback device that constitutes the surveillance camera system 1. However, the present invention is not limited to this. For example, a personal digital assistant (PDA), a mobile phone, or the like can be applied as a moving image playback device.
[0150]
  According to the present embodiment, since the tile boundary distortion is more conspicuous in the still image than in the moving image, the image quality priority mode is selected only for the start frame and the final frame of the moving image, and at high speed and with high accuracy. The distortion of the tile boundary can be suppressed.
In addition, according to the present embodiment, the tile boundary distortion is more conspicuous in the still image than in the moving image. Therefore, by selecting the image quality priority mode for the stop frame related to the stop of the playback of the moving image, the still image can be processed at high speed. The distortion of the tile boundary can be suppressed with high accuracy.
Also, according to the present embodiment, since the frame boundary distortion is conspicuous because the frame with a small code amount has a large compression rate, the image quality priority mode is selected, and since the frame with a large code amount has a small compression rate, the tile boundary distortion is small. Since the speed priority mode is selected because it is inconspicuous, optimal tile boundary distortion smoothing processing is executed for all frames, so that a high-quality reproduced image can be obtained.
In addition, according to the present embodiment, as the frame rate of a moving image increases, tile boundary distortion is less noticeable. Therefore, when the frame rate is larger than a predetermined threshold, the speed priority mode is selected and the frame rate is predetermined. By selecting the image quality priority mode when the threshold value is smaller than the threshold value, it is possible to suppress the distortion of the tile boundary while eliminating an adverse effect such as the frame dropping without the decoding process catching up with the reproduction.
Further, according to the present embodiment, it is possible to suppress the distortion of the tile boundary by a simpler method as compared with the process of smoothing the tile boundary distortion due to the overlap.
Further, according to the present embodiment, since the strength of the low-pass filter is adaptively controlled in the image quality priority mode, the quality is higher than that in the speed priority mode in which a uniform low-pass filter is applied to the pixels. A good image can be reproduced.
Further, according to the present embodiment, it is possible to suppress image quality degradation that occurs when an edge is strong near a tile boundary while suppressing tile boundary distortion.
Further, according to the present embodiment, it is possible to shorten the processing time for suppressing the tile boundary distortion by controlling the tile boundary pixels to be subjected to the low pass filter.
Further, according to the present embodiment, the processing time for suppressing the tile boundary distortion can be shortened by applying the low pass filter only to the tile boundary in the ROI region.
In addition, according to the present embodiment, it is possible to provide an image processing device that exhibits the same effects as the image decoding device of the present invention.
Further, according to the present embodiment, it is possible to provide a moving image display system that exhibits the same effects as the image decoding device of the present invention.
  Also,This embodimentAccording to the above, by causing the computer to read the program stored in the storage medium,Image decoding method of the present inventionThe same effect can be obtained.
  In each embodiment, the surveillance camera 1a including the image input device 2 and the image compression device 3, and the PC 1b including the image expansion device 6 and the image display device 7 which are moving image processing devices are connected via a network 1c. Although the connected surveillance camera system 1 is applied as a moving image display system, the present invention is not limited to this. For example, a digital camera or the like that integrally includes a camera unit that is the image input device 2, a control unit that includes the image compression device 3 and an image expansion device 6 that is a moving image processing device, and a display that is the image display device 7. There is no problem even if it is applied as an image display system.
[0151]
【The invention's effect】
  The present inventionAccording to the present invention, the image quality priority mode that prioritizes the image quality and the speed priority mode that prioritizes the processing speed are appropriately selected and the tile boundary distortion smoothing process is executed.be able to.
[Brief description of the drawings]
FIG. 1 is a functional block diagram of a system that realizes a hierarchical encoding algorithm that is the basis of a JPEG2000 system that is a premise of the present embodiment.
FIG. 2 is an explanatory diagram showing a divided rectangular area of each component of the original image.
FIG. 3 is an explanatory diagram showing subbands at each decomposition level when the number of decomposition levels is 3. FIG.
FIG. 4 is an explanatory diagram showing a precinct.
FIG. 5 is an explanatory diagram showing an example of a procedure for ranking bit planes;
FIG. 6 is an explanatory diagram illustrating a schematic configuration of one frame of code string data.
FIG. 7 is an explanatory diagram showing the concept of Motion JPEG2000.
FIG. 8 is a system configuration diagram showing the surveillance camera system according to the first embodiment of the present invention.
FIG. 9 is a functional block diagram thereof.
FIG. 10 is a block diagram illustrating an example of a hardware configuration of a monitoring camera system.
FIG. 11 is a functional block diagram of an image expansion apparatus.
FIG. 12 is a front view showing a mode designation screen.
FIG. 13 is an explanatory diagram illustrating an example of processing in the first tile boundary smoothing unit and the second tile boundary smoothing unit.
FIG. 14 is an explanatory diagram showing an example of a low-pass filter at a vertical tile boundary by the first tile boundary smoothing means.
FIG. 15 is an explanatory diagram showing an example of a low-pass filter at a horizontal tile boundary by the first tile boundary smoothing means.
FIG. 16 is an explanatory diagram illustrating an example of a low-pass filter in the vicinity of an intersection between a vertical tile boundary and a horizontal tile boundary by the first tile boundary smoothing unit.
FIG. 17 is an explanatory diagram showing an example of a low pass filter at a vertical tile boundary by the second tile boundary smoothing means.
FIG. 18 is an explanatory diagram showing an example of a low-pass filter at a horizontal tile boundary by the second tile boundary smoothing means.
FIG. 19 is an explanatory diagram illustrating an example of a low-pass filter in the vicinity of an intersection between a vertical tile boundary and a horizontal tile boundary by a second tile boundary smoothing unit.
FIG. 20 is an explanatory diagram illustrating an example of a method for calculating a distance between pixels from a tile boundary.
FIG. 21 is an explanatory diagram illustrating an example of an edge amount calculation filter;
FIG. 22 is a functional block diagram of an image expansion apparatus according to a second embodiment of the present invention.
FIG. 23 is an explanatory diagram showing “start frame”, “final frame”, and “stop frame”;
FIG. 24 is a functional block diagram of an image expansion apparatus according to a third embodiment of the present invention.
FIG. 25 is a functional block diagram of an image expansion apparatus according to a fourth embodiment of the present invention.
FIG. 26 is an explanatory diagram illustrating an example of mode selection according to the amount of codes to be decoded.
FIG. 27 is a functional block diagram of an image expansion apparatus according to a fifth embodiment of the present invention.
FIG. 28 is an explanatory diagram showing an example of a process for applying a low-pass filter only to a tile boundary in the ROI region.
FIG. 29 is an explanatory diagram illustrating an example of a process of applying a low pass filter only to the tile boundary in the ROI region.
[Explanation of symbols]
1 Moving image display system
1b Image processing apparatus
2 Image input device
3 Image compression device
6 Image decoding device
7 Image display device
16 storage media
19 Display device
20, 30, 40, 50 Mode selection means
26 Tile boundary smoothing switching means
27, 28 Tile boundary smoothing means
29 Correction tile boundary limiting means
F1-F6 low pass filter

Claims (18)

An image decoding device that continuously decodes a plurality of frames that have been subjected to discrete wavelet transform and compression-coded pixel values for each tile into which an image is divided into a plurality of tiles,
Tile boundary smoothing means for performing a first tile boundary smoothing process or a second tile boundary smoothing process for smoothing distortion of a tile boundary in each frame after decoding;
Mode selection means for selecting an image quality priority mode for prioritizing image quality or a speed priority mode for prioritizing processing speed for the smoothing processing of tile boundary distortion by the tile boundary smoothing means;
For smoothing processing of tile boundary distortion in each frame after decoding by the tile boundary smoothing means, when the speed priority mode is selected according to the selection by the mode selection means, the first tile boundary smoothing A tile boundary smoothing switching means for switching to the second tile boundary smoothing process when the image quality priority mode is selected.
The first tile boundary smoothing process applies a uniform low-pass filter to pixels near the tile boundary in the decoded frame, and the second tile boundary smoothing process includes a tile boundary in the decoded frame. Image decoding characterized by applying a low-pass filter that controls the degree of smoothing to a neighboring pixel as the inter-pixel distance from the tile boundary of the pixel and the edge amount in the diagonal direction of the pixel near the tile boundary increase. apparatus. The mode selection means selects one of the image quality priority mode and the speed priority mode for each frame for smoothing the tile boundary distortion by the tile boundary smoothing means according to the type of frame , the start frame for and the last frame and the image quality priority mode, the image decoding apparatus according to claim 1, characterized in that said speed priority mode in the case of other frames. It said mode selecting means, the image decoding apparatus according to claim 2, wherein also the image quality priority mode for stopping frame according to the stop of the reproduction of the moving image. The mode selection unit selects one of the image quality priority mode and the speed priority mode for each frame in a tile boundary distortion smoothing process by the tile boundary smoothing unit according to a code amount to be decoded for each frame. select, and the image quality priority mode when the decoding target code amount is small, the image decoding according to claim 1, wherein when a large amount of code to be decoded is characterized in that said speed priority mode apparatus. The mode selection means selects one of the image quality priority mode and the speed priority mode for each frame for the tile boundary distortion smoothing processing by the tile boundary smoothing means according to the frame rate , and the frame rate is in the case of less than a predetermined threshold value and the image quality priority mode, the image decoding apparatus according to claim 1, wherein the frame rate if greater than a predetermined threshold value, characterized in that said speed priority mode. A correction tile boundary limiting means for limiting the tile boundary;
The corrected tile boundary limitation means in the vicinity of pixels of the limited tile boundary by only any one of claims 1 to 5, characterized in that to perform the distortion smoothing process tile boundaries by the tile boundary smoothing means An image decoding device according to claim 1. 7. The image decoding apparatus according to claim 6, wherein the tile boundary defined by the corrected tile boundary limiting unit is in a ROI (Region Of Interest) area. The image decoding device according to any one of claims 1 to 7 , wherein a plurality of frames in which pixel values are subjected to discrete wavelet transform and compression-coded for each tile into which an image is divided into a plurality of frames are successively decoded;
An image display device for causing the display device to display an image based on the frame decoded by the image decoding device;
An image processing apparatus comprising: An image input device for capturing moving images;
An image compressing apparatus is divided into a plurality of tiles moving images captured per frame, a discrete wavelet transform compression coding the pixel values for each of the tile by the image input device,
The image decoding device according to any one of claims 1 to 7 , wherein a plurality of frames compressed and encoded by the image compression device are successively decoded;
An image display device for displaying an image based on the decoded frame by the image decoding apparatus on the display device,
A moving image display system comprising: An image decoding method for continuously decoding a plurality of frames in which pixel values are discrete wavelet transformed and compressed and encoded for each tile into which an image is divided into a plurality of tiles,
A tile boundary smoothing step for performing a first tile boundary smoothing process or a second tile boundary smoothing process for smoothing distortion of tile boundaries in each frame after decoding;
A mode selection step of selecting an image quality priority mode that prioritizes image quality or a speed priority mode that prioritizes processing speed for the tile boundary distortion smoothing process in the tile boundary smoothing step;
In the tile boundary distortion smoothing process in each frame after decoding by the tile boundary smoothing step, when the speed priority mode is selected according to the selection by the mode selection step, the first tile boundary smoothing is performed. Switching to processing, and when the image quality priority mode is selected, the tile boundary smoothing switching step for switching to the second tile boundary smoothing processing,
The first tile boundary smoothing process applies a uniform low-pass filter to pixels near the tile boundary in the decoded frame, and the second tile boundary smoothing process includes a tile boundary in the decoded frame. Image decoding characterized by applying a low-pass filter that controls the degree of smoothing to a neighboring pixel as the inter-pixel distance from the tile boundary of the pixel and the edge amount in the diagonal direction of the pixel near the tile boundary increase. Method. The mode selection step selects one of the image quality priority mode and the speed priority mode for each frame for smoothing the tile boundary distortion in the tile boundary smoothing step according to the type of frame , 11. The image decoding method according to claim 10, wherein the first frame and the last frame are set to the image quality priority mode, and the other frames are set to the speed priority mode. It said mode selection step, image decoding method according to claim 11, wherein also the image quality priority mode for stopping frame according to the stop of the reproduction of the moving image. In the mode selection step, one of the image quality priority mode and the speed priority mode is set for each frame in the tile boundary distortion smoothing process in the tile boundary smoothing step according to the code amount to be decoded in each frame. select, and the image quality priority mode when the decoding target code amount is small, the image decoding according to claim 10, wherein when a large amount of code to be decoded is characterized in that said speed priority mode Method. The mode selection step selects one of the image quality priority mode and the speed priority mode for each frame for the tile boundary distortion smoothing process in the tile boundary smoothing step according to a frame rate , and the frame rate is wherein the image quality priority mode, image decoding method according to claim 10, wherein the frame rate if greater than a predetermined threshold value, characterized in that said speed priority mode when more than a predetermined threshold value. A correction tile boundary limiting step for limiting the tile boundary;
The corrected tile boundary limitation neighboring pixels of limited tile boundary in step only, one of the tile boundary smoothing the preceding claims 10, characterized in that to perform the distortion smoothing process tile boundary in step 14 The image decoding method according to one. The image decoding method according to claim 15, wherein the tile boundary defined in the correction tile boundary limiting step is within an ROI (Region Of Interest) region. The computer program for executing the image decoding method of any one of claims 10 to 16. A computer-readable recording medium storing the program according to claim 17 .

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