An improved wavelet denoising algorithm for SAR interferogram using fast non-local means filtering. Issue 27 (13th December 2022)

• Record Type: Journal Article
• Authors: Zhang, Xuedong; Li, Mengwei; Liu, Xianglei; Zhou, Zexu; Wang, Xuedi; Xu, Zidong
• Is Part Of: Geocarto international. Volume 37:Issue 27(2023)
• Page Start: 18600
• Page End: 18617
• Publication Date: 2022-12-13
• Subjects: Interferogram -- wavelet denoising -- fast non-local means filtering -- white noise detection -- threshold function; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2022.2142967
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract: Due to the existence of SAR interferogram noise, the quality of the interferogram is seriously affected. Therefore, to suppress the influence of phase noise, many scholars have carried out a lot of research on SAR interferogram noise reduction, but existing studies have difficulty maintaining edge details while also considering effective noise reduction. Therefore, we proposed an improved wavelet denoising algorithm for SAR interferogram using fast non-local means filtering. The algorithm was divided into three steps. First, the appropriate wavelet basis was selected and the decomposition level was determined by white noise detection to achieve wavelet decomposition. Then, after non-local processing of wavelet coefficients, the threshold denoising rule was constructed by improving the threshold function to achieve the first denoising. Finally, fast non-local means filtering was used for the second denoising. To verify the effectiveness and superiority of the proposed method, experimental verification of simulated data and real data was conducted. Experimental results show that the proposed method can obtain a more ideal SAR interferogram after noise reduction and has better qualitative and quantitative evaluation than the competitive methods, which indicates that the proposed method can achieve effective denoising for SAR interferograms while preserving the detailed features at smaller window settings.