An L0 regularized framelet based model for high-density mixed-impulse noise and Gaussian noise removal

Huasong Chen; Yasong Zhang; Qin Ding; Hao Qiang; Yuanyuan Fan

doi:10.1117/12.2537580

18 November 2019 An L0 regularized framelet based model for high-density mixed-impulse noise and Gaussian noise removal

Huasong Chen, Yasong Zhang, Qin Ding, Hao Qiang, Yuanyuan Fan

Proceedings Volume 11187, Optoelectronic Imaging and Multimedia Technology VI; 111871H (2019) https://doi.org/10.1117/12.2537580
Event: SPIE/COS Photonics Asia, 2019, Hangzhou, China

Abstract

Images are often corrupted by impulse noise due to transmission errors, malfunctioning pixel elements in camera sensors, faulty memory locations in the imaging process. This paper proposes a new method for removing the mixed impulse noise and gaussian noise. The proposed method has two-phase, and the first phase is to identify candidate pixels existing impulse noise by using median filtering. The second phase processes the regions with impulse noise and leaves the others free with a mask generated by the previous phase. In order to protect the sharp image, we propose a L0 regularized framelet with a L1 fidelity term to recover the images. Numerical results demonstrate that the proposed method is a significantly advance over several state-of-the-art techniques on restoration performance.

Citation Download Citation

Huasong Chen, Yasong Zhang, Qin Ding, Hao Qiang, and Yuanyuan Fan "An L0 regularized framelet based model for high-density mixed-impulse noise and Gaussian noise removal", Proc. SPIE 11187, Optoelectronic Imaging and Multimedia Technology VI, 111871H (18 November 2019); https://doi.org/10.1117/12.2537580

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