Method, system and device for detecting SAR image based on ROF model semi-implicit denoising

Abstract

The invention discloses a method, system and device for detecting an SAR image based on ROF model semi-implicit denoising. The method is characterized in that the method comprises the steps: carryingout the logarithmic transformation of two time phase images with noise, and removing the noise of the images with noises through semi-implicit difference scheme via an ROF model after logarithmic transformation; carrying out the difference calculation of the two time phase images with noise, and obtaining a difference image; carrying out the clustering of the difference image, and obtaining a change detection result graph. The method achieves the more accurate and complete obtaining of the change information of a remote sensing image.

Description

technical field [0001] The invention relates to the field of remote sensing images, in particular to a SAR image detection method, system and device based on ROF model semi-implicit denoising. Background technique [0002] At present, remote sensing image change detection technology can help update geographic data, assess disasters, predict disaster development trends, and monitor land use. Due to the influence of various external factors and the limitations of SAR image imaging principles, the collected remote sensing images inevitably introduce a lot of noise. It brings interference to the change detection of the SAR image in the later stage. In order to obtain more accurate change detection information, it is necessary to remove the noise of the SAR image. [0003] Image denoising is a key link in digital image change detection processing, which has strong application value. Currently, denoising methods for SAR images include lee filtering, frost filtering, and morpholo...

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Problems solved by technology

Currently, denoising methods for SAR images include lee filtering, frost filtering, and morphological denoising; there are many image denoising methods in the spatial domain, such as linear filtering, median filtering, and Wiener filtering; image transform domain denoising Methods include: Fourier transform and wavelet transform, etc. In recent years, emerging mathematical methods for denoising have attracted more and more attention from many scholars. In 1992, Rudin, Osher, and Fatemi proposed a total variation (TV) model, namely ROF model; while the explicit solution of the existing ROF model in the process of image denoising has the defects of unstable solution results and long iterations

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