Blind image restoration and segmentation via decoupled adaptive Mumford Shah model

Zhangqin Jiang; Fengwen Mi; Zeyang Dou

doi:10.1117/12.2268142

8 March 2017 Blind image restoration and segmentation via decoupled adaptive Mumford Shah model

Zhangqin Jiang, Fengwen Mi, Zeyang Dou

Proceedings Volume 10255, Selected Papers of the Chinese Society for Optical Engineering Conferences held October and November 2016; 1025544 (2017) https://doi.org/10.1117/12.2268142
Event: Selected Papers of the Chinese Society for Optical Engineering Conferences held October and November 2016, 2016, Jinhua, Suzhou, Chengdu, Xi'an, Wuxi, China

Abstract

A new model that can simultaneously do blind restoration and segmentation task is proposed in the paper. The new model belongs to the variant of Mumford Shah model. In order to promote the computational efficiency, the restoration part and segmentation part are decoupled from the original model. The blind image restoration part is based on the variable exponent regularizer to accurately estimate both piecewise constant point spread functions and smooth point spread functions. The segmentation part is the explicit edge indicator function obtained from the original model. The new model can be efficiently solved using split bregman framework. Numerical experiments show that the new algorithm produces promising results and robust to noise.

Citation Download Citation

Zhangqin Jiang, Fengwen Mi, and Zeyang Dou "Blind image restoration and segmentation via decoupled adaptive Mumford Shah model", Proc. SPIE 10255, Selected Papers of the Chinese Society for Optical Engineering Conferences held October and November 2016, 1025544 (8 March 2017); https://doi.org/10.1117/12.2268142

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