MCS Filter: A Multichannel Structure-Aware Speckle Filter for SAR Images

Synthetic aperture radar (SAR) is widely recognized as an effective tool for investigating oceanic processes, particularly internal wave dynamics, due to its ability to capture high-resolution imaging across diverse environmental conditions. However, speckle noise in SAR imagery poses significant challenges for accurately extracting critical parameters, such as wavefront characteristics and bright-dark distances, thereby hindering its application in detailed internal wave studies. To address this, a novel speckle filtering method is proposed, specifically designed to enhance the quality of SAR images capturing the feature of internal wave. First, a structural description matrix with complex values is introduced to encode pixel value correlations and local spatial features, enabling improved representation of wave-related contextual information within the SAR data. Second, a similarity testing framework based on the Wishart distribution is developed to identify and aggregate structurally similar regions, ensuring robust noise suppression while preserving essential structural parameters. The proposed method strikes a balance between speckle noise reduction and structural preservation, making it adaptable to a variety of SAR datasets. Experimental validation on SAR imagery of oceanic internal waves demonstrates the method’s effectiveness in retaining key internal wave information, while additional tests on terrestrial targets highlight its potential for generalization across different scenarios.