Integrated multi-channel approach for speckle noise reduction in SAR imagery using gradient, spatial, and frequency analysis

Abstract

Synthetic Aperture Radar (SAR) imagery is inherently marred by speckle noise, which undermines image quality and complicates subsequent analytical endeavors. While numerous strategies have been suggested in existing literature to mitigate this unwanted noise, the challenge of eliminating speckle while conserving subtle structural and textural details inherent in the raw data remains unresolved. In this article, we propose a comprehensive approach combining multi-domain analysis with gradient information processing for SAR. Our method aims to effectively suppress speckle noise while retaining crucial image characteristics. By leveraging multi-domain analysis techniques, we exploit both spatial and frequency domain information to gain a deeper insight into image structures. Additionally, we introduce a novel gradient information processing step that utilizes local gradient attributes to guide the process. Experimental results obtained from synthetic and real SAR imagery illustrate the effectiveness of our approach in terms of speckle noise reduction and preservation of image features. Quantitative assessments demonstrate substantial enhancements in image quality, indicating superior performance compared to current state-of-the-art methods.