DocumentCode :
3272649
Title :
Weight optimization for multiple image integration
Author :
Matsuoka, Ryo ; Yamauchi, Takashi ; Baba, Toshihiko ; Okuda, Masumi
Author_Institution :
Fac. of Environ. Eng., Univ. of Kitakyushu, Kitakyushu, Japan
fYear :
2013
fDate :
15-18 Sept. 2013
Firstpage :
795
Lastpage :
799
Abstract :
We propose a denoising technique using multiple image integration. When acquiring a dark scene, the detail of the dark area is often deteriorated by sensor noise. A simple image integration inherently has the capability of reducing random noises. In this paper we develop the denoising performance of the multiple image integration by optimizing weight maps. We determine the optimal weight by solving a convex optimization problem. Through some experimental results, we show the weight optimization significantly improves the de-noising performance.
Keywords :
convex programming; image denoising; convex optimization problem; dark area; dark scene; denoising technique; multiple image integration; weight map optimization; weight optimization; Dynamic range; Noise reduction; Optimization; PSNR; TV; Convex Optimization; Denoising; High Dynamic Range Images; Image Integration;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Image Processing (ICIP), 2013 20th IEEE International Conference on
Conference_Location :
Melbourne, VIC
Type :
conf
DOI :
10.1109/ICIP.2013.6738164
Filename :
6738164
Link To Document :
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