SAR Image Despeckling Using Quadratic-Linear Approximated L1-Norm

2018/01/15 by Fatih Nar, Nar, Fatih
Computer Science · Engineering · #Advanced Image Fusion Techniques #Advanced Image Processing Techniques #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Image and Signal Denoising Methods

paper · pdf · doi:10.48550/arxiv.1801.04751

openalex publication_date 2018/01/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/04

Abstract

Speckle noise, inherent in synthetic aperture radar (SAR) images, degrades the performance of the various SAR image analysis tasks. Thus, speckle noise reduction is a critical preprocessing step for smoothing homogeneous regions while preserving details. This letter proposes a variational despeckling approach where L1-norm total variation regularization term is approximated in a quadratic and linear manner to increase accuracy while decreasing the computation time. Despeckling performance and computational efficiency of the proposed method are shown using synthetic and real-world SAR images.

Citations

• Nonlinear total variation based noise removal algorithms

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