JUST NOTICEABLE DIFFERENCES-BASED VIDEO ENCODING

    公开(公告)号:US20240163436A1

    公开(公告)日:2024-05-16

    申请号:US17988216

    申请日:2022-11-16

    Applicant: Apple Inc.

    CPC classification number: H04N19/124 H04N19/105 H04N19/176 H04N19/61

    Abstract: Techniques are disclosed for achieving quantization in video coding applications that achieves high coding efficiency and retains high image quality. These techniques employ quantization processes using quantization parameters that have been developed according to Just Noticeable Difference (“JND”) models for estimating coding artifacts from video coding. According to these techniques, an input pixel block of video is predictively coded with reference to a prediction reference, and prediction residuals obtained therefrom are transformed to transform domain coefficients. A transform coefficient is quantized by a quantization parameter read from a table populated by JND-quality quantization values, which is indexed by a value representing a statistical analysis of the input pixel block.

    TECHNIQUES FOR CONTOURING/BANDING ARTIFACT REMOVAL IN COMPRESSED IMAGE/VIDEO

    公开(公告)号:US20250142059A1

    公开(公告)日:2025-05-01

    申请号:US18610737

    申请日:2024-03-20

    Applicant: Apple Inc.

    Abstract: Low complexity, hardware-friendly techniques are proposed for video coding systems to mitigate banding artifacts while maintaining the compression efficiency. In general, the proposed techniques consist of two stages including a banding detection stage and a de-banding stage. The banding detection stage may identify the image/video regions where the banding artifact may be present based on gradient information and other information. The de-banding stage may apply corrective techniques to regions identified as likely to possess banding artifacts. In one embodiment, the de-banding adapts the filtering logic proposed by prior video coding standards for other filtering applications to mitigate banding. When implemented over the AV1 video coding standard and the AOM Video Model (AVM) reference software, the proposed technique improves subjective quality significantly at a reasonable hardware implementation cost. The methods and embodiments presented in this document can be beneficial find application in a wide variety of image/video coding standards and systems.

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