Volume 05,Issue 01

State-of-the-art Noise Suppression Methods: A Complete Review

Authors

Noorbakhsh Amiri Golilarz, Ahmad Karambakhsh, Amin Salehpour

Abstract
Many ideas have been implemented for image de-noising and some of these techniques act properly in noise discarding. In this paper, a review of some state-of-the-art noise suppression methods has been presented. These methods were introduced to develop some new strategies to reduce the noise effect from the images by keeping the most important characteristics and discarding small noisy coefficients. In addition, these techniques were conducted to overcome the performance analysis of the previous approaches in terms of acquiring higher Peak Signal to Noise Ratio (PSNR) and to improve the visual quality of the images. In this study, six state-of-the-art unique techniques for image de-noising have been reviewed and their performances have been analyzed. Results show that de-noising based on sparse 3D transform-domain collaborative filtering performs well in comparison with other techniques.

Keyword: Image de-noising, Important characteristics, Small noisy coefficients, 3D transform domain.

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