测绘通报 ›› 2018, Vol. 0 ›› Issue (4): 28-31.doi: 10.13474/j.cnki.11-2246.2018.0105

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Remote Sensing Image Denoising Based on Improved Wavelet Threshold Algorithm

CHEN Zhu'an1,2,3,4, HU Zhifeng1   

  1. 1. Faculty of Geomatics, East China University of Technology, Nanchang 330013, China;
    2. Key Laboratory of Watershed Ecology and Geographical Environment Monitoring, NASG, Nanchang 330013, China;
    3. Jiangxi Province Key Laboratory of Digital Land, Nanchang 330013, China;
    4. Jiangxi Ecological Civilization Construction System Research Center, Nanchang 330013, China
  • Received:2017-07-26 Revised:2017-09-10 Online:2018-04-25 Published:2018-05-03

Abstract:

Based on the research of wavelet threshold denoising method in the literature, an improved method of wavelet threshold denoising is proposed to improve and improve the processing capability and feasibility of wavelet threshold denoising. Combining some of the existing wavelet threshold denoising functions. The threshold function adds a valid adjustment factor to control the variable function. This function not only preserves the corresponding advantages of traditional wavelet hard threshold and soft threshold, but also improves the corresponding precision index. Using this function, threshold denoising not only improves greatly in classical images, but also improves the accuracy of noise detection in remote sensing images. The method evaluates the image by denoising after denoising evaluation mean square error (MSE), peak signal to noise ratio (PSNR), signal to noise ratio (SNR), and root mean square error (RMSE). The improved threshold function method has obviously improved the post-treatment evaluation index for the image.

Key words: wavelet denoising, remote sensing image, improved threshold function, evaluation method

CLC Number: