Abstract
High-bit images can show more detail than low-bit images do. False contours in the low-bit images should be suppressed when converting low-bit images to high-bit ones. In this paper, a contrast-aware bit depth enhancement (BDE) module is proposed based on the visual perceptual feature which models the relationship of contrast sensitivity and image bit depth. And a bit depth enhancement network is constructed by the cascade of this module. The experimental results show that the bit depth enhancement algorithm based on this network structure has the best or second-best peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) metrics when compared with the related algorithms, and on average, our PSNR (40.20 dB) is only 1.03% and SSIM (0.9681) is only 0.11% lower than that of the state-of-the-arts, but uses 6.7% fewer parameters (11.2M). And visual comparisons show that our algorithm can effectively suppress false contours and color distortions, resulting in high-bit images with better quality.
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