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In recent years, display intensity and contrast have increased considerably.Many displays support high dynamic range (HDR) and 10-bit color depth. Sincehigh bit-depth is an emerging technology, video content is still largely shotand transmitted with a bit depth of 8 bits or less per color component.Insufficient bit-depths produce distortions called false contours or banding,and they are visible on high contrast screens. To deal with such distortions,researchers have proposed algorithms for bit-depth enhancement(dequantization). Such techniques convert videos with low bit-depth (LBD) tovideos with high bit-depth (HBD). The quality of converted LBD video, however,is usually lower than that of the original HBD video, and many consumers preferto keep the original HBD versions. In this paper, we propose an algorithm todetermine whether a video has undergone conversion before compression. Thisproblem is complex; it involves detecting outcomes of different dequantizationalgorithms in the presence of compression that strongly affects theleast-significant bits (LSBs) in the video frames. Our algorithm can detectbit-depth enhancement and demonstrates good generalization capability, as it isable to determine whether a video has undergone processing by dequantizationalgorithms absent from the training dataset.

Bit-depth enhancement detection for compressed video