ARTIFACT REDUCTION FOR REMASTERING DYNAMIC RANGE CONTENT USING NEURAL NETWORKS
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United States of America
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Issued Date -
Apr 10, 2025
app pub date -
Oct 6, 2023
filing date -
Oct 6, 2023
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Abstract
In various examples, disclosed techniques use a banding detector neural network to identify the locations and sizes of banding artifacts in pixel regions of an input image. The neural network generates a band size map that identifies at least one banding artifact in the input image. The band size map can include a set of predicted band size values, each of which corresponds to a respective pixel of the input image and represents a distance between edges of a banding artifact. The band size map and the input image are provided as input to a stochastic bilateral blur filter, which generates a de-banded image by applying blurring effects to the input image at the band locations indicated by the band size map. An inverse tone mapping operation is then performed to convert the de-banded image to an image that does not have banding artifacts.
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