Efficient update of cumulative distribution functions for image compression

    公开(公告)号:US12149265B2

    公开(公告)日:2024-11-19

    申请号:US17904030

    申请日:2020-07-06

    Applicant: GOOGLE LLC

    Abstract: Updating cumulative distribution functions (CDFs) during arithmetic encoding can be a challenge because the final element of the CDF should remain fixed during the update calculations. If the probabilities were floating-point numbers, this would not be too much of a challenge; nevertheless, the probabilities and hence the CDFs are represented as integers to take advantage of infinite-precision arithmetic. Some of these difficulties may be alleviated by introducing a “mixing” CDF along with the active CDF being updated; the mixing CDF provides nonlocal context for updating the CDF due to the introduction of a particular symbol in the encoding. Improved techniques of performing arithmetic encoding include updating the CDF using two, one-dimensional mixing CDF arrays: a symbol-dependent array and a symbol-dependent array. The symbol-dependent array is a sub array of a larger, fixed array such that the sub array selected depends on the symbol being used.

    SPARSE MATRIX REPRESENTATION USING A BOUNDARY OF NON-ZERO COEFFICIENTS

    公开(公告)号:US20240080481A1

    公开(公告)日:2024-03-07

    申请号:US18507266

    申请日:2023-11-13

    Applicant: GOOGLE LLC

    Abstract: A sparse matrix representation of image or video data for encoding or decoding uses a boundary of non-zero coefficients within the image or video data. A bounding box encloses each non-zero coefficient within an image or video block. The coefficients enclosed within the bounding box are encoded to a bitstream along with dimensional information usable to identify the bounding box within the image or video block during decoding. Coefficients not enclosed within the bounding box are not specifically encoded within the bitstream. The dimensional information represents one or more of a shape, size, or position within the image or video block of the bounding box. The bounding box may be identified according to a scan order used to process the coefficients within the image or video block. The bounding box may be rectangular or non-rectangular.

    ALPHA CHANNEL PREDICTION
    13.
    发明公开

    公开(公告)号:US20230388534A1

    公开(公告)日:2023-11-30

    申请号:US18448561

    申请日:2023-08-11

    Applicant: GOOGLE LLC

    CPC classification number: H04N19/503 H04N19/186 G06T9/00 H04N19/44 H04N19/20

    Abstract: Image coding using alpha channel prediction may include generating a reconstructed image using alpha channel prediction and outputting the reconstructed image. Generating the reconstructed image using alpha channel prediction may include decoding reconstructed color channel values for a current pixel expressed with reference to first color space, obtaining color space converted color channel values for the current pixel by converting the reconstructed color channel values to a second color space, obtaining an alpha channel lower bound for an alpha channel value for the current pixel using the color space converted color channel values, generating a candidate predicted alpha value for the current pixel, obtaining an adjusted predicted alpha value for the current pixel using the candidate predicted alpha value and the alpha channel lower bound, generating a reconstructed pixel for the current pixel using the adjusted predicted alpha value, and including the reconstructed pixel in the reconstructed image.

    Alpha channel prediction
    14.
    发明授权

    公开(公告)号:US11765377B2

    公开(公告)日:2023-09-19

    申请号:US17994593

    申请日:2022-11-28

    Applicant: GOOGLE LLC

    CPC classification number: H04N19/503 G06T9/00 H04N19/186 H04N19/20 H04N19/44

    Abstract: Image coding using alpha channel prediction may include generating a reconstructed image using alpha channel prediction and outputting the reconstructed image. Generating the reconstructed image using alpha channel prediction may include decoding reconstructed color channel values for a current pixel expressed with reference to first color space, obtaining color space converted color channel values for the current pixel by converting the reconstructed color channel values to a second color space, obtaining an alpha channel lower bound for an alpha channel value for the current pixel using the color space converted color channel values, generating a candidate predicted alpha value for the current pixel, obtaining an adjusted predicted alpha value for the current pixel using the candidate predicted alpha value and the alpha channel lower bound, generating a reconstructed pixel for the current pixel using the adjusted predicted alpha value, and including the reconstructed pixel in the reconstructed image.

    Sparse Matrix Representation Using a Boundary of Non-Zero Coefficients

    公开(公告)号:US20220353533A1

    公开(公告)日:2022-11-03

    申请号:US17860693

    申请日:2022-07-08

    Applicant: GOOGLE LLC

    Abstract: A sparse matrix representation of image or video data for encoding or decoding uses a boundary of non-zero coefficients within the image or video data. A bounding box encloses each non-zero coefficient within an image or video block. The coefficients enclosed within the bounding box are encoded to a bitstream along with dimensional information usable to identify the bounding box within the image or video block during decoding. Coefficients not enclosed within the bounding box are not specifically encoded within the bitstream. The dimensional information represents one or more of a shape, size, or position within the image or video block of the bounding box. The bounding box may be identified according to a scan order used to process the coefficients within the image or video block. The bounding box may be rectangular or non-rectangular.

    Image coding using lexicographic coding order with floating block-partitioning

    公开(公告)号:US11012714B1

    公开(公告)日:2021-05-18

    申请号:US16909221

    申请日:2020-06-23

    Applicant: GOOGLE LLC

    Abstract: Decoding image data using lexicographic coding order with floating block-partitioning includes obtaining, from an encoded bitstream, encoded data for a defined portion of a frame, generating a reconstructed frame by decoding the encoded data, and outputting the reconstructed frame for presentation to a user. Decoding the encoded data using lexicographic coding order with floating block-partitioning includes decoding, from the encoded data, block dimension data for respective blocks from the plurality of blocks in lexicographic coding order, determining block location data for the respective blocks from the plurality of blocks in lexicographic coding order, generating reconstructed block data for the respective blocks from the plurality of blocks using the block dimension data and the block location data by decoding, from the encoded data, image content data for the respective blocks from the plurality of blocks, and including the reconstructed block data in the reconstructed frame.

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