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
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;
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
DOI :
10.1109/SOPO.2010.5504345