@inproceedings{b4c0de52d7d74f8d8bf6fd8b3f169cec,
title = "A new image denoising and enhancement method combining the nonsubsampled contourlet transform and improved total variation",
abstract = "Transform-based denoising methods are very popular in recent years. However, they often suffer from unwanted artifacts like pesudo-Gibbs phenomena. In this paper, we propose a new hybrid image denoising by combining the nonsubsumpled contourlet transform (NSCT) with improved total variation. First, an improved stark function which integrates noise reduction with feature enhancement is developed to nonlinearly shrink and stretch the NSCT coefficients. Then an improved Total variation is introduced to reduce the pseudo-Gibbs artifacts of the enhanced image which are caused by the elimination of small NSCT coefficients. Numerical experiments show that this approach improves the image quality by enhancing the shape of edges and important detailed features while suppressing noise in comparison to many well known methods.",
keywords = "image denoising, image enhancement, nonsubsumpled contourlet transform, total variation",
author = "Ying Li and Yu Jia and Yanning Zhang",
year = "2013",
doi = "10.1007/978-3-642-42057-3_108",
language = "英语",
isbn = "9783642420566",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "860--867",
booktitle = "Intelligence Science and Big Data Engineering - 4th International Conference, IScIDE 2013, Revised Selected Papers",
note = "4th International Conference on Intelligence Science and Big Data Engineering, IScIDE 2013 ; Conference date: 31-07-2013 Through 02-08-2013",
}