DocumentCode
2940076
Title
Improving Image Enhancement by Gradient Fusion
Author
Xu, Xin ; Chen, Qiang ; Xia, Deshen
Author_Institution
Sch. of Comput. Sci. & Technol., Nanjing Univ. of Sci. & Technol., Nanjing, China
fYear
2010
fDate
19-21 June 2010
Firstpage
1
Lastpage
4
Abstract
We present a fusion approach in the gradient domain to combine complementary advantages between image enhancement results for visualization improvement. A weighted structure tensor is employed to capture significant details of each input channel, and local contrast is incorporated in the design of fusion weights. Experimental results demonstrate that the fused image can preserve significant detail and structural information of each input image, and the visual effect is improved.
Keywords
data visualisation; gradient methods; image enhancement; image fusion; gradient fusion; image enhancement; visualization improvement; weighted structure tensor; Computer science; Data mining; Dynamic range; Frequency domain analysis; Histograms; Humans; Image enhancement; Image fusion; Lighting; Tensile stress;
fLanguage
English
Publisher
ieee
Conference_Titel
Photonics and Optoelectronic (SOPO), 2010 Symposium on
Conference_Location
Chengdu
Print_ISBN
978-1-4244-4963-7
Electronic_ISBN
978-1-4244-4964-4
Type
conf
DOI
10.1109/SOPO.2010.5504345
Filename
5504345
Link To Document