@inproceedings{1bf838f471614e818e42e9f81937a2ba,
title = "Image de-quantization via spatially varying sparsity prior",
abstract = "We address the problem of image de-quantization, which is also known as bit-depth expansion if the reconstructed 2D signal is re-quantized into higher bit-precision. In this paper, a novel image de-quantization method based on convex optimization theory is proposed, which exploits the spatially varying characteristics of image surface. We test our method on image bit-depth expansion problems, and the experimental results show that proposed method can achieve superior PSNR and SSIM performance.",
keywords = "De-quantization, Image bit-depth expansion, L-L optimization",
author = "Pengfei Wan and Au, \{Oscar C.\} and Ketan Tang and Yuanfang Guo",
year = "2012",
doi = "10.1109/ICIP.2012.6467019",
language = "英语",
isbn = "9781467325332",
series = "Proceedings - International Conference on Image Processing, ICIP",
pages = "953--956",
booktitle = "2012 IEEE International Conference on Image Processing, ICIP 2012 - Proceedings",
note = "2012 19th IEEE International Conference on Image Processing, ICIP 2012 ; Conference date: 30-09-2012 Through 03-10-2012",
}