Infrared image enhancement through saliency feature analysis based on multi-scale decomposition |
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| Institution: | 1. Electronics and Information College, Hangzhou Dianzi University, Xiasha Campus, Hangzhou 310018, China;2. State Key Lab of Modern Optical Instrumentation, Zhejiang University, Hangzhou 310027, China;1. School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China;2. State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China;1. School of Computer Engineering and Science, Shanghai University, Shanghai 200444, China;2. School of Information Engineering, Inner Mongolia University of Science and Technology, Baotou 014010, China;1. Department of Information Engineering, Engineering University of Armed Police Force, Xi’an 710086, China;2. Department of Electronics Technology, Engineering University of Armed Police Force, Xi’an 710086, China;1. School of Electronics and Information, Northwestern Polytechnical University, Xi’an 710072, China;2. School of Information Science and Technology, Northwest University, Xi’an 710069, China |
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| Abstract: | To improve contrast between dim target region and background in infrared (IR) long-range surveillance, this paper proposes a fast image enhancement approach using saliency feature extraction based on multi-scale decomposition. Firstly, a smooth based multi-scale decomposition is designed and applied to original infrared image, generating sub-images with various frequency components at different decomposition levels. The dim target regions of sub-images are extracted by a local frequency-tuned based saliency feature detection method, secondly. With saliency maps created by saliency extraction using multi-scale local windows with different sizes, the sub-images are enhanced at different decomposition scales. Finally, the enhanced result is reconstructed by synthesizing the all sub-images with adjustable synthetic weights. Since salient areas are analyzed based on fast multi-scale image decomposition, IR image can be s enhanced with good contrast successfully and rapidly. Compared with other algorithms, the experimental results prove that the proposed method is robust and efficient for IR image enhancement. |
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| Keywords: | Infrared image enhancement Saliency feature analysis Multi-scale decomposition Local frequency-tuned |
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