MULTICOLOR LOSSLESS IMAGE COMPRESSION
    1.
    发明公开

    公开(公告)号:US20230316578A1

    公开(公告)日:2023-10-05

    申请号:US18001694

    申请日:2020-09-30

    Applicant: GOOGLE LLC

    CPC classification number: G06T9/00

    Abstract: A method including receiving an image targeted for compression into a compressed image, identifying a coding line including a plurality of elements, each of the plurality of elements having a color, selecting an element from the plurality of elements from the coding line in the image, determining a presented color associated with the selected element, comparing the presented color to an expected color, and in response to determining the presented color is not the expected color inserting a marker into a data structure representing a portion of the compressed image, the marker indicating that the presented color is not the expected color, determining an encoding value corresponding to the presented color, and inserting the encoding value into the data structure representing the compressed image.

    Alpha Channel Prediction
    2.
    发明申请

    公开(公告)号:US20230090481A1

    公开(公告)日:2023-03-23

    申请号:US17994593

    申请日:2022-11-28

    Applicant: GOOGLE LLC

    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.

    Dynamic Bitset Coding
    3.
    发明公开

    公开(公告)号:US20230199222A1

    公开(公告)日:2023-06-22

    申请号:US17926831

    申请日:2020-05-28

    Applicant: Google LLC

    CPC classification number: H04N19/70 H04N19/184 H04N19/157

    Abstract: Decoding a bitset, each bit of the bitset corresponding to a respective value in a range of a minimum value to a maximum value, includes decoding, from a compressed bitstream, indexes of bits of the bitset, each bit of the bits having a first value. Decoding the bitset also includes setting all other bits of the bitset not decoded from the compressed bitstream to a second value. Decoding the indexes of bits of the bitset includes decoding a number of the indexes of the bits of the bitset, decoding a first index of the indexes in a first range having a first lower bound and a first upper bound, and decoding a last index of the indexes in a second range having a second lower bound and a second upper bound.

    Alpha channel prediction
    4.
    发明授权

    公开(公告)号:US11528498B2

    公开(公告)日:2022-12-13

    申请号:US17354562

    申请日:2021-06-22

    Applicant: Google LLC

    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:US11388439B2

    公开(公告)日:2022-07-12

    申请号:US16726408

    申请日:2019-12-24

    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
    6.
    发明申请

    公开(公告)号:US20220014773A1

    公开(公告)日:2022-01-13

    申请号:US17354562

    申请日:2021-06-22

    Applicant: Google LLC

    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:US20210120270A1

    公开(公告)日:2021-04-22

    申请号:US16726408

    申请日:2019-12-24

    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.

    Sparse matrix representation using a boundary of non-zero coefficients

    公开(公告)号:US11818397B2

    公开(公告)日:2023-11-14

    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.

    Dynamic Method for Symbol Encoding
    9.
    发明公开

    公开(公告)号:US20230188726A1

    公开(公告)日:2023-06-15

    申请号:US17922306

    申请日:2020-06-16

    Applicant: Google LLC

    CPC classification number: H04N19/149 H04N19/182 H04N19/186 H04N19/46

    Abstract: Encoding an image includes determining respective costs of coding a symbol using available coding types. A first coding type indicates that a value of the symbol is to be decoded using a same number of bits, and a second coding type indicates that the value of the symbol is to be decoded using a range. An optimal coding type of the available coding types is selected, which corresponds to a smallest cost of the respective costs. A first indicator of the optimal coding type and a first symbol value of the symbol using the optimal coding type are encoded in a compressed bitstream. Decoding an image includes decoding, from a header of a compressed bitstream, respective coding types of symbols encoded in the compressed bitstream and decoding, from the compressed bitstream, respective values of the symbols according to the respective coding types decoded from the header.

    EFFICIENT UPDATE OF CUMULATIVE DISTRIBUTION FUNCTIONS FOR IMAGE COMPRESSION

    公开(公告)号:US20230085142A1

    公开(公告)日:2023-03-16

    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.

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