Contrast-enhanced fusion of infrared and visible images

Wenshan Ding; Duyan Bi; Linyuan He; Zunlin Fan

doi:10.1117/1.OE.57.9.093111

27 September 2018 Contrast-enhanced fusion of infrared and visible images

Wenshan Ding, Duyan Bi, Linyuan He, Zunlin Fan

Author Affiliations +

Funded by: National Natural Science Foundation of China (NSFC)

Optical Engineering, Vol. 57, Issue 9, 093111 (September 2018). https://doi.org/10.1117/1.OE.57.9.093111

Abstract

The fusion of infrared and visible images may result in low contrast, which is unsuitable for observation by human eyes. Thus, we propose a contrast-enhanced fusion algorithm with nonsubsampled shearlet transform (NSST) frames, in which the NSST is first employed to decompose each of the source images into one low frequency sub-band and a series of high frequency sub-bands. To improve the fusion performance, we designed two measures for fusion of the low frequency and the high frequency: the low frequency is divided into salient and nonsalient regions in accordance with the human visual system to improve the global contrast by targeted fusion and the high frequency requires a local contrast fusion strategy. Finally, the merged sub-bands are constructed according to the selection principles, and the final fused image is produced by applying the inverse NSST on these merged sub-bands. Experimental results demonstrate the effectiveness and superiority of the proposed method over the state-of-the-art fusion methods in terms of both visual effect and objective evaluation results.

Citation Download Citation

Wenshan Ding, Duyan Bi, Linyuan He, and Zunlin Fan "Contrast-enhanced fusion of infrared and visible images," Optical Engineering 57(9), 093111 (27 September 2018). https://doi.org/10.1117/1.OE.57.9.093111

Received: 20 June 2018; Accepted: 11 September 2018; Published: 27 September 2018

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