WO2015146586A1 - 画像復号化装置および画像復号化方法 - Google Patents

画像復号化装置および画像復号化方法 Download PDF

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WO2015146586A1
WO2015146586A1 PCT/JP2015/057133 JP2015057133W WO2015146586A1 WO 2015146586 A1 WO2015146586 A1 WO 2015146586A1 JP 2015057133 W JP2015057133 W JP 2015057133W WO 2015146586 A1 WO2015146586 A1 WO 2015146586A1
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roi
mask
image data
image
data
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French (fr)
Japanese (ja)
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水野　雄介
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MegaChips Corp
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MegaChips Corp
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/63—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets
    • H04N19/64—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets characterised by ordering of coefficients or of bits for transmission
    • H04N19/647—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets characterised by ordering of coefficients or of bits for transmission using significance based coding, e.g. Embedded Zerotrees of Wavelets [EZW] or Set Partitioning in Hierarchical Trees [SPIHT]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/117—Filters, e.g. for pre-processing or post-processing
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/13—Adaptive entropy coding, e.g. adaptive variable length coding [AVLC] or context adaptive binary arithmetic coding [CABAC]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/167—Position within a video image, e.g. region of interest [ROI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/172—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a picture, frame or field
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/60—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding
    • H04N19/63—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using transform coding using sub-band based transform, e.g. wavelets
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/124—Quantisation
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
    • H04N19/146—Data rate or code amount at the encoder output
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/30—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using hierarchical techniques, e.g. scalability
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/46—Embedding additional information in the video signal during the compression process

Definitions

  • the present invention relates to an image decoding technique, and more particularly to a technique for decoding an image including a region of interest (ROI).
  • ROI region of interest
  • Non-Patent Document 1 relating to JPEG (Joint Photographic Experts Group) 2000 discloses encoding and decoding of an image including an ROI. Specifically, the Max-shift method is disclosed. Also disclosed is a method of developing the ROI on the wavelet plane.
  • Patent Document 1 discloses a method of developing which coefficients belong to the ROI on the wavelet plane, although the type is different from the wavelet filter employed in JPEG2000.
  • Patent Documents 2 to 6 listed below also disclose image processing techniques relating to images including ROI.
  • JP-T-2001-520466 JP 2006-203409 A Special Table 2002-528007 JP 2006-295299 A JP 2006-279397 A JP 2011-166695 A
  • the present invention is capable of cutting out a new image processing technique related to ROI, more specifically, a region designated as ROI in an original image and adjusting the boundary of the region to be cut out.
  • the purpose is to provide technology.
  • the image decoding device extracts a coded image data and additional information related to a scaling amount of the Max-shift method from a bit stream encoded using wavelet transform.
  • a stream analysis unit and decoding the encoded image data to generate quantized image data composed of a plurality of quantized wavelet coefficients; a decoding unit; and a plurality of quantized wavelet coefficients Based on the scaling amount, it is determined whether each is associated with an ROI (region of interest) or a non-ROI in the original image, and the determination result corresponds to the decomposition level of the quantized image data.
  • An ROI processing unit for generating an ROI mask, and the quantized image data after the scale-down processing based on the scaling amount Inverse quantization is performed to generate first image data composed of a plurality of wavelet coefficients, and an inverse quantization unit and the first image data are acquired, and the first image data is obtained.
  • an inverse wavelet transform unit that generates second image data at a specified decomposition level and the ROI mask are acquired, and a predetermined mask restoration process is performed on the ROI mask.
  • a mask restoration unit that generates a restoration ROI mask having the same decomposition level as the second image data by performing the plurality of times, and applying the restoration ROI mask to the second image data.
  • the inverse wavelet transform unit generates a resolution level 0 for the masked image data.
  • An image decoding device is the image decoding device according to the first aspect, wherein the designated decomposition level is the same as the decomposition level of the first image data.
  • the inverse wavelet transform unit supplies the first image data instead of the second image data to the mask execution unit, and the mask restoration unit uses the ROI mask instead of the restored ROI mask. Supplying to the mask execution unit, the mask execution unit generates the masked image data by applying the ROI mask to the first image data.
  • An image decoding apparatus is the image decoding apparatus according to the first or second aspect, wherein the mask is used when the specified decomposition level is decomposition level 0.
  • the processed image data is handled as the decoded image data without being subjected to the inverse wavelet transform.
  • An image decoding apparatus is the image decoding apparatus according to any one of the first to third aspects, wherein the ROI mask and the restored ROI mask are The ROI corresponding to the ROI and the non-ROI and the non-ROI corresponding portion in the original image, and the mask execution unit sets the data set in the non-ROI corresponding portion in the image data to be masked Replace with 0.
  • An image decoding apparatus is the image decoding apparatus according to any one of the first to third aspects, wherein the ROI mask and the restored ROI mask are The ROI corresponding to the ROI and the non-ROI and the non-ROI corresponding portion in the original image, and the mask execution unit sets the data set in the non-ROI corresponding portion in the image data to be masked , Replace with other data about another original image.
  • An image decoding device is the image decoding device according to any one of the first to fifth aspects, wherein the predetermined mask restoration processing is performed in a predetermined manner. This is a process for generating a second ROI mask whose decomposition level is one step lower than that of the first ROI mask from the first ROI mask to be restored based on the mask restoration condition of 5 ⁇ 3 filter for the inverse wavelet transform.
  • the predetermined mask restoration condition in this case is that n is an integer, and the nth of the low frequency component and the ⁇ n ⁇ 1 ⁇ th and nth data of the high frequency component before the inverse wavelet transform
  • the 2nth data is A first condition that the second ROI mask is formed so as to be associated with the ROI, and the nth and ⁇ n + 1 ⁇ th of the low frequency components and the ⁇ n ⁇ of the high frequency components before the inverse wavelet transform
  • the ⁇ 2n + 1 ⁇ th data is added to the ROI after the inverse wavelet transform.
  • a second condition that the second ROI mask is formed so as to be associated with each other.
  • An image decoding device is the image decoding device according to any one of the first to fifth aspects, wherein the predetermined mask restoration processing is performed in a predetermined manner. This is a process for generating a second ROI mask whose decomposition level is one step lower than that of the first ROI mask from the first ROI mask to be restored on the basis of the mask restoration condition, and a Daubechies 9 ⁇ 7 filter is used for the inverse wavelet transform.
  • the predetermined mask restoration condition is that n is an integer and ⁇ n-1 ⁇ to ⁇ n + 1 ⁇ th of the low frequency component and ⁇ n-2 ⁇ of the high frequency component before the inverse wavelet transform
  • An image decoding device is the image decoding device according to any one of the first to seventh aspects, wherein the bit stream is JPEG (Joint Photographic Experts). Group) 2000.
  • JPEG Joint Photographic Experts. Group
  • An image decoding device is the image decoding device according to any one of the first to eighth aspects, wherein the predetermined mask restoration processing is performed a plurality of times. Performing includes recursively performing the predetermined mask restoration processing a plurality of times.
  • the image decoding method extracts (a) encoded image data and additional information related to the scaling amount of the Max-shift method from a bitstream encoded using wavelet transform. And (b) generating quantized image data composed of a plurality of quantized wavelet coefficients by decoding the encoded image data; and (c) the plurality of quantized wavelets. Whether each of the coefficients is associated with an ROI (region of interest) or a non-ROI in the original image is determined based on the scaling amount, and from the determination result, the decomposition level of the quantized image data is determined. Generating a corresponding ROI mask; and (d) inversely processing the quantized image data after the scale-down processing based on the scaling amount.
  • (E) acquiring the first image data and performing inverse wavelet transform on the first image data by generating a first image data composed of a plurality of wavelet coefficients
  • (F) acquiring the ROI mask and performing a predetermined mask restoration process once or a plurality of times on the ROI mask.
  • Generating a restored ROI mask having the same decomposition level as the second image data and (g) generating masked image data by applying the restored ROI mask to the second image data.
  • (H) generating decoded image data by performing the inverse wavelet transform on the masked image data up to a decomposition level of 0; Equipped with a.
  • An image decoding method is the image decoding method according to the tenth aspect described above, wherein (i) the designated decomposition level is a decomposition level of the first image data.
  • the method further includes the step of generating the masked image data by applying the ROI mask to the first image data, instead of the step (g).
  • An image decoding method is the image decoding method according to the tenth or eleventh aspect, wherein the mask is used when the specified decomposition level is a decomposition level 0. Processed image data is handled as the decoded image data without performing the inverse wavelet transform.
  • An image decoding method is the image decoding method according to any one of the tenth to twelfth aspects, wherein the ROI mask and the restored ROI mask are Data that includes an ROI corresponding portion and a non-ROI corresponding portion corresponding to the ROI and the non-ROI in the original image, and the masked image data is set as the non-ROI corresponding portion in the image data to be masked Is generated by replacing 0 with 0.
  • An image decoding method is the image decoding method according to any one of the tenth to twelfth aspects, wherein the ROI mask and the restored ROI mask are Data that includes an ROI corresponding portion and a non-ROI corresponding portion corresponding to the ROI and the non-ROI in the original image, and the masked image data is set as the non-ROI corresponding portion in the image data to be masked Is replaced with another data relating to another original image.
  • An image decoding method is the image decoding method according to any one of the tenth to fourteenth aspects, wherein the predetermined mask restoration process This is a process for generating a second ROI mask whose decomposition level is one step lower than that of the first ROI mask from the first ROI mask to be restored based on the mask restoration condition of 5 ⁇ 3 filter for the inverse wavelet transform.
  • the predetermined mask restoration condition in this case is that n is an integer, and the nth of the low frequency component and the ⁇ n ⁇ 1 ⁇ th and nth data of the high frequency component before the inverse wavelet transform When at least one is associated with the ROI in the original image by the first ROI mask, the 2nth data after the inverse wavelet transform.
  • the second ROI mask so as to be associated with the ROI, and before the inverse wavelet transform, the nth and ⁇ n + 1 ⁇ th of the low-frequency components and the ⁇
  • the nth and ⁇ n + 1 ⁇ th of the low-frequency components are associated with the ROI by the first ROI mask, the ⁇ 2n + 1 ⁇ th data after the inverse wavelet transform And a second condition that the second ROI mask is formed so as to be associated with the ROI.
  • An image decoding method is the image decoding method according to any one of the tenth to fourteenth aspects described above, wherein the predetermined mask restoration process is a predetermined one.
  • This is a process for generating a second ROI mask whose decomposition level is one step lower than that of the first ROI mask from the first ROI mask to be restored on the basis of the mask restoration condition, and a Daubechies 9 ⁇ 7 filter is used for the inverse wavelet transform.
  • the predetermined mask restoration condition is that n is an integer and ⁇ n-1 ⁇ to ⁇ n + 1 ⁇ th of the low frequency component and ⁇ n-2 ⁇ of the high frequency component before the inverse wavelet transform
  • n is an integer and ⁇ n-1 ⁇ to ⁇ n + 1 ⁇ th of the low frequency component and ⁇ n-2 ⁇ of the high frequency component before the inverse wavelet transform
  • An image decoding method is the image decoding method according to any one of the tenth to sixteenth aspects, wherein the bitstream is JPEG (Joint Photographic Experts). Group) 2000.
  • An image decoding method is the image decoding method according to any one of the tenth to seventeenth aspects described above, wherein the predetermined mask is used in the step (f).
  • Performing the restoration process a plurality of times includes recursively performing the predetermined mask restoration process a plurality of times.
  • the boundary of the region to be cut out from the original image can be adjusted according to the designated decomposition level value.
  • the Max-shift method since the Max-shift method is used, it is not necessary to obtain ROI mask data separately. Similar effects can also be obtained by the second to ninth aspects quoting the first aspect and the eleventh to eighteenth aspects quoting the tenth aspect.
  • restoration part. It is a flowchart explaining a mask execution part. It is a decoded image when the specified value of the decomposition level 4.
  • the image encoding device will be described first, and then the image decoding device will be described.
  • encoding is employed for compression of image data, and therefore, “compression” and “encoding” may be used synonymously.
  • the image coding apparatus may be called, for example, an image compression apparatus or an image compression coding apparatus.
  • the image decoding apparatus may be called, for example, an image expansion apparatus or an image expansion decoding apparatus.
  • FIG. 1 illustrates a block diagram of an image encoding device.
  • An image encoding device 10 illustrated in FIG. 1 includes a preprocessing unit 20, a wavelet transform unit (hereinafter also referred to as a DWT unit) 30, a quantization unit 40, an ROI management unit 50, and an encoding unit 60.
  • a bit stream generation unit 70 is a preprocessing unit 20
  • a wavelet transform unit hereinafter also referred to as a DWT unit
  • the preprocessing unit 20 performs predetermined preprocessing on the input image data to be compressed.
  • the preprocessing unit 20 includes a DC level shift unit 21, a color space conversion unit 22, and a tiling unit 23.
  • the DC level shift unit 21 converts the DC level of the input image data as necessary.
  • the color space conversion unit 22 converts the color space of the image data after DC level conversion. For example, the RGB component is converted into a YCbCr component (consisting of a luminance component Y and color difference components Cb and Cr).
  • the tiling unit 23 divides the image data after color space conversion into a plurality of rectangular region components called “tiles”. Then, the tiling unit 23 supplies image data to the DWT unit 30 for each tile. It is not always necessary to divide the image data into tiles, and the image data for one frame output from the color space conversion unit 22 may be supplied to the DWT unit 30 as it is.
  • the DWT unit 30 subjects the image data supplied from the tiling unit 23 to integer type or real type discrete wavelet transform (DWT) in units of tiles, and outputs conversion coefficients obtained as a result.
  • the transform coefficient may be referred to as, for example, a wavelet transform coefficient or a wavelet coefficient.
  • DWT two-dimensional image data is decomposed into a high frequency component (in other words, a high frequency component) and a low frequency component (in other words, a low frequency component).
  • frequency decomposition is also called, for example, band division.
  • Each band component obtained by frequency decomposition (that is, each of a low-frequency component and a high-frequency component) is also referred to as a subband.
  • the basic method of JPEG 2000 employs an octave division method that recursively divides a band component only in the low frequency side in both the vertical direction and the horizontal direction. The number of recursive band divisions is called a decomposition level.
  • Figures 2 to 4 show mallat wavelet planes for two-dimensional DWT.
  • the input image two-dimensional image
  • the input image is subjected to frequency decomposition for each of the vertical direction and the horizontal direction at decomposition level 1 (see FIG. 2).
  • decomposition level 1 see FIG. 2.
  • FIG. 2 it is decomposed into four band components HH1, HL1, LH1, and LL1.
  • the band component LL1 obtained at the decomposition level 1 is further decomposed into four band components HH2, HL2, LH2, and LL2 at the decomposition level 2 (see FIG. 3).
  • the band component LL2 obtained at the decomposition level 2 is further decomposed into four band components HH3, HL3, LH3, and LL3 at the decomposition level 3 (see FIG. 4).
  • the set value of the decomposition level is not limited to 3.
  • HL1 is a band component composed of a horizontal high-frequency component H and a vertical low-frequency component L at the decomposition level 1.
  • the notation is generalized as “XYm” (X and Y are either H or L. m is an integer of 1 or more). That is, the band component composed of the horizontal band component X and the vertical band component Y at the decomposition level m is denoted as “XYm”.
  • the wavelet plane (see FIGS. 2 to 4) is a data group in which DWT calculation result data is two-dimensionally arranged in association with the pixels in the original image.
  • the calculation result data (LL component data) obtained by using a certain pixel in the original image as the target pixel is the value of the target pixel in the original image. It is arranged according to the position.
  • the wavelet plane is sometimes called a wavelet space, a wavelet region, or a wavelet image.
  • the band component LL1 corresponds to the essential information of the image.
  • the band component LL1 it is possible to provide an image having a size that is 1/4 of the image before the decomposition.
  • the band component HL1 corresponds to edge information extending in the vertical direction
  • the band component LH1 corresponds to edge information extending in the horizontal direction
  • the band component HH corresponds to information on an edge extending in an oblique direction.
  • FIG. 7 shows a configuration example of a two-divided filter bank group that realizes a one-dimensional DWT.
  • the two-divided filter bank includes a low-pass filter H 0 (z) that passes a low-frequency component, a high-pass filter H 1 (z) that passes a high-frequency component, and filters H 0 (z) and H 1. (Z) and a down sampler provided at each subsequent stage. Note that the down sampler thins out every other input signal, and outputs the signal by halving the signal length.
  • One-dimensional DWT is realized by repeatedly using this two-divided filter bank.
  • the quantization unit 40 performs scalar quantization on the wavelet coefficients supplied from the DWT unit 30 based on the quantization step size.
  • the quantization step size is set according to the target image quality, for example. Further, the quantization unit 40 performs bit shift for prioritizing the image quality of the ROI based on the ROI setting information supplied from the ROI management unit 50.
  • a typical method of using ROI is the Max-shift method as an optional function of JPEG2000.
  • the ROI can be specified in an arbitrary form.
  • the ROI is compressed to high image quality, while the non-ROI is compressed to low image quality.
  • the maximum value max (Mb) is determined from the wavelet coefficients corresponding to the non-ROI.
  • s (referred to as a scaling value) that satisfies s ⁇ max (Mb) is obtained.
  • MSB most significant bit
  • the value of the wavelet coefficient corresponding to the ROI is relatively scaled up by 2 s .
  • a wavelet coefficient corresponding to the ROI may be referred to as a ROI coefficient
  • a wavelet coefficient corresponding to the non-ROI may be referred to as a non-ROI coefficient.
  • the compression rate of ROI can be set lower than that of non-ROI, and high-quality compressed data can be obtained for ROI.
  • the ROI management unit 50 supplies the ROI setting information to the quantization unit 40 as described above.
  • the ROI setting information is provided by a so-called ROI mask. Note that the ROI mask may be simply referred to as a mask.
  • the ROI mask used for the scale-up in the quantization unit 40 is a bitmap corresponding to the wavelet plane.
  • the bits of the bit map are provided corresponding to the wavelet coefficients on the wavelet plane, and the state of each bit indicates whether the corresponding wavelet coefficient corresponds to ROI or non-ROI.
  • the ROI mask corresponding to the wavelet plane can be generated, for example, by developing the ROI mask corresponding to the original image on the wavelet plane.
  • Each bit of the ROI mask corresponding to the original image corresponds to a pixel of the original image.
  • the ROI mask corresponding to the original image may be referred to as an original image level (in other words, decomposition level 0) ROI mask, original ROI mask, or original mask, for example.
  • the ROI mask developed on the wavelet plane may be called, for example, a developed ROI mask or a developed mask.
  • the ROI mask at the original image level can be created, for example, by designating an ROI (or non-ROI) with a pointing input device such as a mouse for the original image displayed on the display.
  • the original image data may be analyzed, and a region including a specific color (for example, flower color) in the original image may be extracted as the ROI.
  • Other techniques may be used to generate the original mask.
  • FIG. 9 shows an original mask 100 when the flower region is designated as the ROI in the original image of FIG.
  • the white portion is the ROI corresponding portion 101 corresponding to the ROI on the original image
  • the black portion is the non-ROI corresponding portion 102 corresponding to the non-ROI on the original image.
  • developed masks 110, 120, and 130 in which the original mask 100 of FIG. 9 is developed on the wavelet planes of decomposition levels 1, 2, and 3 are shown in FIGS.
  • the ROI corresponding portions 111, 121, and 131 are illustrated in white
  • the non-ROI corresponding portions 112, 122, and 132 are illustrated in black.
  • the method of developing the ROI mask 100 at the original image level on the wavelet plane depends on the number of taps of the DWT filter.
  • the original mask can be developed as shown in FIG.
  • the decomposition-side low-pass filter has 5 taps
  • the decomposition-side high-pass filter has 3 taps.
  • n can be expressed as 2nth, where n is an integer
  • pixel data belongs to ROI
  • the low-frequency component side (example in FIG. 7)
  • the nth data (among the data output from the downsampler on the low pass filter side) is set in the ROI corresponding portion 111 in the expansion mask 110 at the decomposition level 1.
  • the high-frequency component side (referring to the example in FIG. 7), the ⁇ n ⁇ 1 ⁇ -th and n-th data are divided into decomposition level 1 (of the data output from the downsampler on the high-pass filter side).
  • the nth and ⁇ n + 1 ⁇ th data on the low frequency component side and ⁇ n ⁇ on the high frequency component side 1 ⁇ th to ⁇ n + 1 ⁇ th data are set in the ROI corresponding portion 111 in the development mask 101 at the decomposition level 1.
  • FIG. 13 illustrates the correspondence between the original image and the decomposition level 1 wavelet plane, but the recursive expansion to a deeper hierarchy can be similarly understood.
  • the original mask can be developed as shown in FIG.
  • the decomposition-side low-pass filter has 9 taps
  • the decomposition-side high-pass filter has 7 taps.
  • the ⁇ n ⁇ 1 ⁇ -th to ⁇ n + 2 ⁇ -th data on the low-frequency component side and the high-frequency component side The ⁇ n ⁇ 2 ⁇ th to ⁇ n + 2 ⁇ th data are set in the ROI corresponding portion 111 in the expansion mask 110 at the decomposition level 1.
  • the ROI management unit 50 generates a development mask corresponding to the set value of the decomposition level from the original mask 100 given in advance.
  • a development mask for each decomposition level may be given to the ROI management unit 50 in advance.
  • the expansion mask is used by the quantizing unit 40 to determine whether each wavelet coefficient is an ROI coefficient. Such determination may be performed by the quantization unit 40 or the ROI management unit 50.
  • the encoding unit 60 performs predetermined encoding on the quantized wavelet coefficient (scaled by the Max-shift method here) generated by the quantizing unit 40.
  • predetermined encoding for example, entropy encoding is performed according to EBCOT (Embedded Block Coding with Optimized Truncation) that performs bit-plane encoding.
  • the encoding unit 60 includes a coefficient bit modeling unit 61 and an entropy encoding unit 62.
  • the coefficient bit modeling unit 61 performs a bit modeling process on the quantized wavelet coefficients.
  • bit modeling process uses a known technique, and detailed description thereof is omitted.
  • the coefficient bit modeling unit 61 divides the input band component into areas called “code blocks” of about 32 ⁇ 32 or 64 ⁇ 64. Then, the coefficient bit modeling unit 61 assigns each bit value constituting the binary value of each quantized wavelet coefficient in the code block to a separate bit plane. The bit modeling process is performed in units of such bit planes.
  • the entropy encoding unit 62 performs entropy encoding on the data generated by the coefficient bit modeling unit 61 to generate encoded image data.
  • entropy coding for example, known arithmetic coding is used.
  • the encoding unit 60 may control the code amount by performing rate control on the encoded image data generated by the entropy encoding unit 62.
  • bit stream generation unit 70 multiplexes the encoded image data output from the encoding unit 60 with additional information to generate a bit stream compliant with JPEG2000, and outputs the bit stream as compressed image data.
  • additional information for example, header information, layer configuration, scalability information, quantization table, scaling amount applied by the Max-shift method can be cited.
  • FIG. 15 illustrates a block diagram of the image decoding apparatus.
  • An image decoding apparatus 200 illustrated in FIG. 15 includes a bitstream analysis unit 210, a decoding unit 220, an ROI processing unit 230, an inverse quantization unit 240, and an inverse wavelet transform unit (hereinafter also referred to as an IDWT unit). ) 250, a mask processing unit 260, and a post-processing unit 270.
  • the bit stream analysis unit 210 analyzes the bit stream 300 compliant with JPEG2000, and extracts the encoded image data 302 and additional information from the bit stream 300.
  • the encoded data 302 is supplied to the decoding unit 220.
  • Various kinds of additional information are respectively supplied to predetermined processing units.
  • the additional information 304 regarding the scaling amount of the Max-shift method is supplied to the ROI processing unit 230.
  • the additional information 304 may be referred to as a scaling amount 304.
  • the decoding unit 220 performs predetermined decoding on the encoded image data 302.
  • the predetermined decoding basically corresponds to the process opposite to the encoding in the encoding unit 60 in FIG. 1 except for the code amount control.
  • quantized image data 308 composed of quantized wavelet coefficients is generated from the encoded image data.
  • the decoding unit 220 includes an entropy decoding unit 221 and a coefficient bit modeling unit 222.
  • the entropy decoding unit 221 performs entropy decoding on the encoded image data 302 to generate bit data 306.
  • the entropy decoding corresponds to a process opposite to the entropy encoding in the entropy encoding unit 62 in FIG.
  • the coefficient bit modeling unit 222 performs a bit modeling process on the bit data 306 generated by the entropy decoding unit 221 to restore the quantized wavelet coefficients. Thereby, quantized image data 308 is generated.
  • the bit modeling process here corresponds to a process opposite to that in the coefficient bit modeling unit 61 of FIG.
  • the quantized image data 308 generated by the coefficient bit modeling unit 222 is supplied to the ROI processing unit 230 and the inverse quantization unit 240.
  • FIG. 16 shows a flowchart of the processing S10 performed by the ROI processing unit 230.
  • the ROI processing unit 230 associates each of the plurality of quantized wavelet coefficients included in the quantized image data 308 with either the ROI or the non-ROI in the original image. Is determined based on the scaling amount 304.
  • each quantized wavelet coefficient is compared with 2 s .
  • a quantized wavelet coefficient larger than 2 s is determined to be a scaled-up coefficient (in other words, ROI coefficient).
  • quantized wavelet coefficients of 2 s or less are determined to be unscaled coefficients (in other words, non-ROI coefficients).
  • step S12 the ROI processing unit 230 bit-shifts the quantized wavelet coefficient determined to be scaled up to the least significant bit (LSB) side by s bits. That is, a scale-down process based on the scaling amount 304 is performed on the target quantized wavelet coefficient.
  • LSB least significant bit
  • Quantized image data 310 after step S12 is supplied to the inverse quantization unit 240.
  • the scaling amount 304 acquired from the bitstream analysis unit 210 may be the scaling value s or the value (that is, 2 s ). It may be.
  • step S13 the ROI processing unit 230 generates an ROI mask (that is, a development mask) 312 corresponding to the decomposition level of the quantized image data based on the determination result in step S11. Specifically, as described above, in step S11, it is determined whether each quantized wavelet coefficient is associated with an ROI coefficient or a non-ROI coefficient. Therefore, the development mask 312 can be generated by mapping the determination result.
  • an ROI mask that is, a development mask
  • the expansion mask generated in step S13 corresponds to the expansion mask used by the quantization unit 40 of the image encoding device 10 to select the quantized wavelet coefficients to be scaled up.
  • the ROI mask 312 generated in step S13 is supplied to the mask processing unit 260.
  • the ROI processing unit 230 does not execute the processing S10. Even in that case, according to the example of FIG. 15, the quantized wavelet coefficients are supplied to the inverse quantization unit 240 from the decoding unit 220.
  • the ROI processing unit 230 may set the scaling amount to 0 and execute the processing S10. In that case, unlike the example of FIG. 15, the supply of the quantized wavelet coefficient from the decoding unit 220 to the inverse quantization unit 240 can be omitted.
  • the input bitstream 300 does not include the scaling amount 304, the input image does not include the ROI, and thus the mask generation step S13 may not be executed.
  • bit shift step S12 may be executed by the inverse quantization unit 240. Even in that case, the mask generation step S13 is executed by the ROI processing unit 230.
  • the coefficient determination step S11 may be executed by at least one of the inverse quantization unit 240 and the ROI processing unit 230.
  • the inverse quantization unit 240 performs scalar inverse quantization on the quantized image data 308 or 310 supplied from the decoding unit 220 or the ROI processing unit 230.
  • the inverse quantization here corresponds to the reverse process of the quantization in the quantization unit 40 of FIG.
  • the quantized wavelet coefficients are converted into wavelet coefficients by inverse quantization, and as a result, first image data 314 composed of a plurality of wavelet coefficients is generated.
  • the first image data 314 is supplied to the IDWT unit 250.
  • the IDWT unit 250 performs integer type or real type inverse discrete wavelet transform (IDWT).
  • IDWT integer type or real type inverse discrete wavelet transform
  • the band components are recursively synthesized in the reverse process of the DWT in the DWT unit 30 of FIG.
  • IDWT is also performed in units of the same tiles.
  • Band synthesis by IDWT can be realized by a two-divided filter bank group that realizes one-dimensional IDWT.
  • the two-divided filter bank illustrated in FIG. 18 includes a low-pass filter G 0 (z) that passes low-frequency components, a high-pass filter G 1 (z) that passes high-frequency components, and filters G 0 (z) and G 1.
  • the up-sampler provided in each preceding stage of (z) and an adder for adding the outputs of the filters G 0 (z) and G 1 (z).
  • the upsampler inserts one zero value between the input signals, and doubles the signal length for output.
  • One-dimensional IDWT is realized by repeatedly using this two-divided filter bank.
  • the number of synthesis in IDWT is called a synthesis level. Note that the synthesis level is not limited to the example of FIG. Note that the combined level of the state before IDWT (the state of decomposition level 3 in the example of FIG. 18) is expressed as 0.
  • the IDWT unit 250 acquires the first image data 314 from the inverse quantization unit 240, and performs IDWT once or a plurality of times on the first image data 314, whereby the specified decomposition level is obtained.
  • Second image data 320 is generated.
  • the specified value 316 of the decomposition level of the second image data 320 is given to the IDWT unit 250 and the mask processing unit 260.
  • the second image data 320 is converted into masked image data 322 by the mask processing unit 260.
  • the IDWT unit 250 performs IDWT on the masked image data 322 up to the decomposition level 0, thereby generating image data 324 at the decomposition level 0, that is, decoded image data 324.
  • the decoded image data 324 is supplied to the post-processing unit 270.
  • FIG. 19 shows a block diagram of the mask processing unit 260.
  • the mask processing unit 260 includes a mask restoration unit 261 and a mask execution unit 262.
  • the mask restoration unit 261 acquires the ROI mask 312 from the ROI processing unit 230 and also acquires the specified value 316 of the decomposition level of the second image data 320. Then, the mask restoration unit 261 generates a ROI mask 318 having the same decomposition level as that of the second image data 320 by performing predetermined mask restoration processing once or a plurality of times on the ROI mask 312.
  • the ROI mask 318 may be referred to as a restoration ROI mask 318 or a restoration mask 318, for example.
  • the designated value 316 is a value that designates the decomposition level of the second image data 320 delivered from the IDWT unit 250 to the mask processing unit 260, and to which decomposition level the ROI mask 312 generated by the ROI processing unit 230 is restored. It is also a value that specifies.
  • the designated value 316 is assumed to be given in advance to the image decoding apparatus 200, for example.
  • the designated value 316 may be fixed or may be changeable by a user or the like.
  • the ROI mask 312 generated by the ROI processing unit 230 corresponds to decomposition level 3. (See FIG. 12).
  • the mask restoration unit 261 restores the ROI mask 120 in FIG.
  • the mask restoration unit 261 restores the ROI mask 110 in FIG.
  • the mask restoration unit 261 restores the ROI mask 100 in FIG.
  • the above-described predetermined mask restoration processing is based on a predetermined mask restoration condition, and an ROI mask (also called a second ROI mask) whose decomposition level is one step lower than that of the first ROI mask from the ROI mask to be restored (also called a first ROI mask). This process generates a mask.
  • an ROI mask also called a second ROI mask
  • This process generates a mask.
  • the above-described predetermined mask restoration condition depends on the number of taps of the IDWT filter, in other words, the number of taps of the DWT filter in the image encoding device 10.
  • the predetermined mask restoration condition includes the following first condition and second condition (see FIG. 20).
  • the decomposition-side low-pass filter has 5 taps
  • the decomposition-side high-pass filter has 3 taps.
  • the first condition is that at least one of the n-th low-frequency component and the ⁇ n-1 ⁇ -th and n-th data of the high-frequency component is associated with the ROI in the original image by the first ROI mask before the IDWT.
  • the second ROI mask is defined so that the 2n-th data is associated with the ROI after IDWT. Note that n is an integer.
  • the second condition is that at least one of the nth and ⁇ n + 1 ⁇ th low-frequency components and the ⁇ n-1 ⁇ -th to ⁇ n + 1 ⁇ -th data of the high frequency components before the IDWT is determined by the first ROI mask.
  • the second ROI mask is formed so that the ⁇ 2n + 1 ⁇ -th data is associated with the ROI after the IDWT.
  • the predetermined mask restoration condition includes the following third condition and fourth condition (see FIG. 21).
  • the decomposition-side low-pass filter has 9 taps
  • the decomposition-side high-pass filter has 7 taps.
  • the third condition is that at least one of the ⁇ n-1 ⁇ th to ⁇ n + 1 ⁇ th data of the low frequency component and the ⁇ n-2 ⁇ th to ⁇ n + 1 ⁇ th data of the high frequency component before the IDWT is the first ROI.
  • the mask is associated with the ROI in the original image, it is defined that the second ROI mask is formed so that the 2n-th data is associated with the ROI after the IDWT.
  • the fourth condition is that at least one of the ⁇ n ⁇ 1 ⁇ th to ⁇ n + 2 ⁇ th of the low frequency component and the ⁇ n ⁇ 2 ⁇ th to ⁇ n + 2 ⁇ th data of the high frequency component before IDWT is: It is defined that when the first ROI mask is associated with the ROI, the second ROI mask is formed so that the ⁇ 2n + 1 ⁇ -th data is associated with the ROI after the IDWT.
  • the above-described predetermined mask restoration processing is performed once or a plurality of times according to the designated value 316 of the decomposition level, whereby the restoration ROI mask 318 having the decomposition level designated by the designated value 316 can be generated.
  • the predetermined mask restoration process is performed a plurality of times, the predetermined mask restoration process can be recursively performed a plurality of times.
  • FIG. 22 is a flowchart showing the process S20 performed by the mask restoration unit 261.
  • the current decomposition level of the ROI mask (in other words, the decomposition level of the first ROI mask) is compared with the decomposition level designated by the designated value 316.
  • the current decomposition level of the ROI mask is greater than the specified value 316
  • the current ROI mask is restored by one stage in step S22. That is, an ROI mask (in other words, the second ROI mask) whose decomposition level is one step lower is generated. And process S21 is performed again.
  • process S20 is terminated.
  • process S30 (see FIG. 23) is executed.
  • the mask execution unit 262 obtains the restoration ROI mask 318 at the decomposition level designated by the designated value 316 from the mask restoration unit 261. Also, the mask execution unit 262 acquires the second image data 320 at the decomposition level specified by the specified value 316 from the IDWT unit 250. Then, the mask execution unit 262 generates masked image data 322 by applying the restoration ROI mask 318 to the second image data 320.
  • FIG. 23 is a flowchart showing the process S30 performed by the mask execution unit 262. According to the example of FIG. 23, in step S31, it is determined whether or not the wavelet coefficient in the second image data 320 acquired from the IDWT unit 250 is set in the ROI corresponding part in the restored ROI mask 318.
  • the wavelet coefficient determined not to be set in the ROI corresponding part (in other words, the non-ROI coefficient) is subjected to data replacement in step S32.
  • data replacement is not performed for the wavelet coefficient determined to be set to the ROI corresponding part (in other words, the ROI coefficient).
  • the mask execution unit 262 performs the process S30 on all wavelet coefficients in the second image data 320. Thereby, masked image data 322 is generated from the second image data 320.
  • the masked image data 322 is delivered to the IDWT unit 250.
  • the IDWT unit 250 performs the IDWT on the masked image data 322 up to the decomposition level 0, thereby generating the image data 324 at the decomposition level 0, that is, the decoded image data 324.
  • the post-processing unit 270 performs predetermined post-processing on the decoded image data 324 output from the IDWT unit 250.
  • the predetermined post-process corresponds to a process opposite to the predetermined pre-process in the image encoding device 10 of FIG.
  • the post-processing unit 270 includes a tiling unit 271, a color space conversion unit 272, and a DC level shift unit 273.
  • the tiling unit 271 performs processing reverse to that of the tiling unit 23 of the image encoding device 10 in FIG. Specifically, the tiling unit 271 generates the image data 326 for one frame by combining the decoded image data 324 in units of tiles output from the IDWT unit 250. Note that if the decoded image data 324 is not supplied in units of tiles, in other words, if DWT is not performed in units of tiles, the processing by the tiling unit 271 is omitted. Alternatively, the tiling part 271 itself may be omitted.
  • the color space conversion unit 272 performs processing reverse to that of the color space conversion unit 22 of the image encoding device 10 of FIG.
  • the image data 326 output from the tiling unit 271 is converted into RGB components.
  • the DC level shift unit 273 converts the DC level of the image data 328 output from the color space conversion unit 272 as necessary.
  • the image data 330 output from the DC level shift unit 273 is output image data of the image decoding device 200.
  • the example in which the IDWT unit 250 generates the second image data 320 at the specified decomposition level by performing IDWT one or more times on the first image data 314 has been described above. That is, in this example, the decomposition level of the second image data 320 (specified by the specified value 316) is lower than the decomposition level of the first image data 314.
  • the IDWT unit 250 does not perform DWT on the first image data 314 acquired from the inverse quantization unit 240, and uses the first image data 314 as a mask execution unit instead of the second image data 320. 262.
  • the mask restoration unit 261 does not perform a predetermined mask restoration process on the ROI mask 312 acquired from the ROI processing unit 230, and uses the ROI mask 312 instead of the restoration ROI mask 318 as a mask execution unit 262. To supply.
  • the mask execution unit 262 generates masked image data 322 by applying the ROI mask 312 to the first image data 314.
  • the decomposition level 0 it is possible to designate the decomposition level 0 as the designated value 316.
  • the decomposition level of the second image data 320 supplied to the mask execution unit 262 is zero.
  • the second image data 320 is not composed of wavelet coefficients, but is composed of pixel values of, for example, YCbCr components.
  • the masked image data 322 since the masked image data 322 is also at the decomposition level 0, it is not necessary to perform IDWT, and the masked image data 322 is handled as the decoded image data 324.
  • the mask execution unit 262 may pass the masked image data 322 to the IDWT unit 250 or may pass it to the post-processing unit 270.
  • the encoded image data 302 included in the bit stream 300 is band-divided up to the decomposition level 5.
  • FIG. 29 shows an image obtained by decoding the encoded image data 302 by a conventional method.
  • the image decoding apparatus 200 can cut out the region designated as the ROI in the original image of FIG. Further, as can be seen by comparing FIGS. 24 to 28, the smaller the specified value 316 of the decomposition level, the closer the region cut out from the original image is to the ROI. In other words, the boundary of the area cut out from the original image can be adjusted by setting the designated value 316.
  • step S32 corresponds to an example in which the non-ROI coefficient is replaced with 0 in step S32 (see FIG. 23).
  • an area that is not cut out from the original image can be a black background. However, it may be replaced with a predetermined value other than 0.
  • non-ROI coefficients may be replaced with different values.
  • an image can be synthesized by replacing a non-ROI coefficient with another wavelet coefficient generated from another original image.
  • a composite image in which a flower region is overlaid on another original image can be obtained.
  • the image decoding apparatus 200 since the ROI mask is generated from the input image data to which the Max-shift method is applied, it is not necessary to obtain the ROI mask data separately.
  • the masked image data 322 can be subjected to IDWT up to the decomposition level 0 (that is, the masked image data 322). Even if the decoded image data 324 is generated from the image data, the ROI in the decoded image data is not affected.
  • the third condition and the fourth condition the same applies to the third condition and the fourth condition.
  • the image decoding apparatus 200 provides the above processing and effects for a bitstream that is encoded using wavelet transform and includes encoded image data and additional information related to the scaling amount of the Max-shift method. .
  • the various processing units of the image decoding device 200 are configured by hardware, but some or all of the various processing units may be configured by a program that causes a microprocessor to function.
  • ROI masks 101, 111, 121, 131 ROI compatible parts 102, 112, 122, 132 Non-ROI compatible parts 200
  • Image decoding device 210 Bit stream analysis unit 220 Decoding unit 230 ROI processing unit 240 Inverse Quantization unit 250 Inverse wavelet transform unit 260 Mask processing unit 261 Mask restoration unit 262 Mask execution unit 300 Bit stream 302 Encoded image data 304 Scaling amount 308 Quantized image data 310 Scaled down quantized image data 312 ROI mask 314 First image data 316 Decomposition level specified value 318 Restored ROI mask 320 Second image data 322 Masked image data 324 Decoded image data

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