Guidance-Aided Triple-Adaptive Frost Filter for Speckle Suppression in the Synthetic Aperture Radar Image

Author:

Li JiamuORCID,Yu WenboORCID,Wang Yi,Wang Zijian,Xiao Jiarong,Yu ZhongjunORCID,Zhang Desheng

Abstract

Speckle noise exists inherently in the synthetic aperture radar (SAR) image. Its multiplicative property leads to lots of difficulties in SAR image processing. A novel guidance-aided triple-adaptive Frost filter is proposed in this paper, which has potential for real-time processing platforms. Firstly, a scale-adaptive sliding window sizing method is adopted to determine the neighborhood ranges for every point in the image. All the subsequent processing is based on it. Then, an adaptive calculation for the tuning factor in the Frost filter is embedded into the proposed method. Lastly, the feature information apertured from the original image is used to provide guidance for edge recovery automatically, which guarantees the satisfactory ability for feature preservation. Thus, a novel improved Frost filter is proposed with triple adaptabilities. Both the positioning accuracy and response sensitivity of the scale-adaptive sliding window sizing method are verified first. The superiority of the adaptive tuning factor combined with the scale-adaptive sliding window is confirmed by two comparison experiments. At last, the results of speckle suppression experiments on the synthetic images and two natural airborne SAR images present a better performance than other methods.

Publisher

MDPI AG

Subject

General Earth and Planetary Sciences

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Research on SAR image denoising method based on feature extraction;Electronics Letters;2024-04

2. A novel Lee filtering algorithm based on adaptive size sliding window;Fourth International Conference on Geology, Mapping, and Remote Sensing (ICGMRS 2023);2024-01-23

3. A novel speckle-robust feature map and research on rotation invariance of feature maps in the SAR image;Third International Conference on Computer Vision and Pattern Analysis (ICCPA 2023);2023-08-01

4. An Algorithmic Approach towards Remote Sensing Imagery Data Restoration Using Guided Filters in Real-Time Applications;Canadian Journal of Remote Sensing;2023-07-12

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