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Proceedings Paper

Color image fusion based on simplified pulse coupled neural network and HSV color space
Author(s): Jin Xin; Dongming Zhou; Shaowen Yao; Rencan Nie; Chuanbo Yu; Tingting Ding
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Paper Abstract

Using the simplified pulse coupled neural network (S-PCNN) model and hue, saturation and value (HSV) color space, an effective color image fusion algorithm was proposed in this paper. In the HSV color space, using S-PCNN, the feature region clustering of each component (H, S, V) was done; the fusion of the various components of the different source images based on the oscillation frequency graph (OFG) was achieved; then through the inverse HSV transform to get RGB color image, the fusion of the color image were realized. Experimental results show that the algorithm both in the subjective visual effect and objective evaluation criteria is superior to other common color image fusion algorithms.

Paper Details

Date Published: 29 August 2016
PDF: 5 pages
Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003321 (29 August 2016); doi: 10.1117/12.2244474
Show Author Affiliations
Jin Xin, Yunnan Univ. (China)
Dongming Zhou, Yunnan Univ. (China)
Shaowen Yao, Yunnan Univ. (China)
Rencan Nie, Yunnan Univ. (China)
Chuanbo Yu, Yunnan Univ. (China)
Tingting Ding, Yunnan Univ. (China)


Published in SPIE Proceedings Vol. 10033:
Eighth International Conference on Digital Image Processing (ICDIP 2016)
Charles M. Falco; Xudong Jiang, Editor(s)

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