Adaptive fuzzy threshold method wavelet denoising of GF-2 satellite image

doi:10.13474/j.cnki.11-2246.2019.0073

Abstract

Abstract: GF-2 satellite images provide abundant image information,and the releasing of high-resolution image data has broken the long-term dependence of China's high resolution data on land observation.However,the image can be disturbed in the process of transmission and preservation,and if the area of interest is polluted,the image information in the region cannot be fully used.In order to solve the difficult problem of the GF-2 remote sensing image denoising,this paper adopts adaptive fuzzy threshold denoising methods,which is based on various scales noise variance adaptive fuzzy threshold function of nonlinear processing,restructuring as a new wavelet coefficients,the denoised image is obtained by inverse transformation of the wavelet.Compared with average filtering,gaussian smoothing filter,median filter,filtering,wavelet threshold denoising and Birge-Massart strategy denoising threshold value method,the results show that the adaptive fuzzy threshold denoising method is fully combined with hard and soft threshold processing method that both retains the image details and makes the image more smooth.The image that is denoised by this method can preserve overall information,the denoising effect is highly desirable.

Key words: remote sensing, GF-2 satellite, wavelet analysis, adaptive threshold, image denoising

CLC Number:

P237

ZHANG Yuhang, YANG Wunian, REN Jintong, DENG Xiaoyu. Adaptive fuzzy threshold method wavelet denoising of GF-2 satellite image[J]. 测绘通报, 2019, 0(3): 32-35.

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