Title :
Multichannel image restoration based on optimization of the structural similarity index
Author :
Temerinac-Ott, Maja ; Burkhardt, Hans
Author_Institution :
Inst. of Comput. Sci., Univ. of Freiburg, Freiburg, Germany
Abstract :
In this paper a framework for multichannel image restoration based on optimization of the structural similarity (SSIM) index is presented. The SSIM index describes the similarity of images more appropriately for the human visual system than the mean square error (MSE). It has not yet been explored for the multi channel restoration task. The construction of an optimization algorithm is difficult due to the non-linearity of the SSIM measure. The existing solution based on a quasi-convex problem formulation is successfully extended for the multichannel image restoration. The correctness of the algorithm is verified on sample images and it is shown that multi-view information can significantly improve the restoration results.
Keywords :
image restoration; mean square error methods; optimisation; MSE; SSIM index; human visual system; mean square error; multichannel image restoration; multichannel restoration task; optimization algorithm; quasi-convex problem formulation; structural similarity index; Biology; Computer science; Humans; Image processing; Image reconstruction; Image restoration; Licenses; Mean square error methods; Pattern recognition; Signal processing; inverse filter; multichannel image restoration; quasi-convex optimization of non-linear functions; structural similarity;
Conference_Titel :
Signals, Systems and Computers, 2009 Conference Record of the Forty-Third Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
978-1-4244-5825-7
DOI :
10.1109/ACSSC.2009.5469973
