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