Synthetic Aperture Radar image nonlinear enhancement algorithm based on NSCT transform |
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| Institution: | 1. State Key Laboratory of Precision Measuring Technology and Instruments, Tianjin University, China;2. College of Electronic and Communication Engineering, Tianjin Normal University, China;1. Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xidian University, Xi’an 710071, China;2. College of Science, Inner Mongolia University of Technology, Inner Mongolia 010051, China;1. Department of Electrical and Computer Engineering, Texas A&M University at Qatar, Doha, Qatar;2. Department of Electrical and Computer Engineering, University of Manitoba, Canada;3. Department of Electrical and Computer Engineering, Texas A&M University, College Station, TX, United States;4. Computer, Electrical, and Mathematical Science and Engineering (CEMSE) Division, King Abdullah University of Science and Technology, Saudi Arabia |
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| Abstract: | Due to the imaging mechanism, Synthetic Aperture Radar (SAR) images are susceptible to speckle noise, which affects radar image interpretation. So image denoising and enhancement are important topics of improving SAR image performance. A nonlinear image enhancement algorithm based on nonsubsampled contourlet transform (NSCT) is proposed in this paper. The image is decomposed into coefficients of different scales and directions through nonsubsampled contourlet transform. It is denoised by the threshold method of the multi-scale product of NSCT coefficients. Then thresholds of the nonlinear enhancement function are determined according to the coefficients of each scale. The two parameters of the function, among which one is used to control the range of enhancement and the other can determine the strength of enhancement, are obtained by solving nonlinear equations. The coefficients processed by the enhancement function are used to reconstruct the image. The simulation results on the Matlab platform show that the algorithm has a good effect of enhancing details of images and suppressing noise signals meanwhile. |
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| Keywords: | Image enhancement Contourlet transform NSCT Multi-scale product |
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