| Technology Application |
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Self-adaptive restoration for remote sensing noise images based on improved NAS-RIF algorithm |
| ZHANG Fan |
| Department of Information Management, Henan Vocational College of Economics and Trade, Zhengzhou 450018, China |
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Abstract Image restoration is an important research content in remote sensing noise image processing. In order to deal with the remote sensing image effectively, this paper proposes a new improved self-adaptive NAS-RIF algorithm based on the research on the basic principle of the non-negativity and support constraints recursive inverse filtering (NAS-RIF). With the purpose of tackling the defects of the original NAS-RIF algorithm,the author first filtered the image with pepper and salt noise as well as white Gaussian noise by the self-adaptive pseudo-median filtering algorithm so as to eliminate the noise in the image as much as possible, then improved the original NAS-RIF algorithm effectively from two aspects of support domain and background gray value,in combinatiuon with the gray values of the image and finally introduced the correction term based on the target information to the cost function so as to improve the classic cost function of the original NAS-RIF algorithm. Aimed at improving the convergence of the cost function of the improved NAS-RIF algorithm,the author combined the logarithmic function and adopted the conjugate gradient method to optimize the improved NAS-RIF algorithm. Subjective and objective analysis of the simulation experimental results shows that the performance of the improved NAS-RIF algorithm proposed in this paper is better than that of the original NAS-RIF algorithm and some available improved NAS-RIF algorithms as well as the wavelet threshold denoising method,suggesting that this means is suitable for the restoration process of the remote sensing noise image.
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VIS/NIR
multispectral camera
index set
application requirements
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Issue Date: 02 March 2015
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2015,
Vol. 27
