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Proceedings Paper

A visible/infrared gray image fusion algorithm based on the YUV color transformation
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Paper Abstract

Color fusion technology, one of the typical technologies, has been emphasized all over the world. Multiband images are fused into a color image. Some effective visible and thermal infrared color fusion algorithms have been proposed now. We have successfully run a real-time natural sense of visible/infrared color fusion algorithm in DSP and FPGA hardware processing platforms. However, according to different needs, gray image fusion technology has its own unique applications. Based on the natural sense of color image fusion algorithm of the visible and infrared, we have proposed a visible / infrared gray image fusion algorithm. Firstly we do a YUV color fusion. Then we output the brightness of the fusion as gray fusion images. This algorithm for image fusion is compared with typical fusion algorithms: the weighted average, the Laplace Pyramid and the Haar basis wavelet. Several objective evaluation indicators are selected. The results of objective and subjective comparison show that the algorithm has most advantages. It shows that multiband gray image fusion in the color space is available. The algorithm is implemented on a DSP hardware image processing platform real-time with the TI's chip as the kernel processor. It makes natural sense of color fusion and gray fusion for visible light (low level light) and thermal imaging integrated. Users are convenient to choose model of the natural sense of color fusion or gray fusion for real-time video imaging output

Paper Details

Date Published: 30 November 2012
PDF: 9 pages
Proc. SPIE 8558, Optoelectronic Imaging and Multimedia Technology II, 855814 (30 November 2012); doi: 10.1117/12.2001309
Show Author Affiliations
Jin Zhu, Beijing Institute of Technology (China)
Weiqi Jin, Beijing Institute of Technology (China)
Jiakun Li, Beijing Institute of Technology (China)
Li Li, Beijing Institute of Technology (China)

Published in SPIE Proceedings Vol. 8558:
Optoelectronic Imaging and Multimedia Technology II
Tsutomu Shimura; Guangyu Xu; Linmi Tao; Jesse Zheng, Editor(s)

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