Color image fusion based on simplified pulse coupled neural network and HSV color space

Jin Xin; Dongming Zhou; Shaowen Yao; Rencan Nie; Chuanbo Yu; Tingting Ding

doi:10.1117/12.2244474

29 August 2016 Color image fusion based on simplified pulse coupled neural network and HSV color space

Jin Xin, Dongming Zhou, Shaowen Yao, Rencan Nie, Chuanbo Yu, Tingting Ding

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 1003321 (2016) https://doi.org/10.1117/12.2244474
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

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.

Citation Download Citation

Jin Xin, Dongming Zhou, Shaowen Yao, Rencan Nie, Chuanbo Yu, and Tingting Ding "Color image fusion based on simplified pulse coupled neural network and HSV color space", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 1003321 (29 August 2016); https://doi.org/10.1117/12.2244474

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KEYWORDS

Image fusion

RGB color model

Neurons

Neural networks

Image processing

Principal component analysis

Visualization

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