Removing False Contour Artifact for Bit-depth Expansion

Bit-depth expansion is a process of enhancing the image quality by increasing the number of intensity levels. To solve this problem, a hybrid method is proposed, where the pixels are categorized into smooth and complex regions, and are processed using different methods. The pixels in the smooth region are reconstructed with a smooth prior, and a Bayesian estimator is used for the pixels in the complex region. The proposed method effectively removes the false contour artifacts while requiring less computation than conventional methods. In addition, the method shows good quantitative performance, and the PSNR gains over the best existing method are 1.45 dB and 0.26 dB for 4 bits and 3 bits expansion cases, respectively.