What is it about?
Synthetic Aperture Radar (SAR) images are degraded with speckle noise which makes manual and automatic interpretation of these images difficult. Proposed method (SDD-QL) provides a fast and accurate mechanism for reducing speckle noise by smoothing homogeneous regions while keeping the details such as point scatterers or edges of the regions.
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Why is it important?
Proposed method is accurate, fast, easy to implement, and parallelizable which are important since the number of SAR sensors and thus images are increasing.
Perspectives
This study uses a variational approach for speckle noise reduction since variational approaches are among the successful methods for noise reduction in the literature. However, solving the variational cost function in and efficient and accurate manner is challenging. There are various approaches for the minimization of variational cost functions but they require great effort to understand and implement. Despite, this paper introduces a simple and elegant way to improve the speckle reduction accuracy while also improving the speed. Proposed numerical approach can be easily applied to other image processing problems within variational framework.
Fatih Nar
Read the Original
This page is a summary of: SAR Image Despeckling using Quadratic-Linear Approximated L1-Norm , Electronics Letters, January 2018, the Institution of Engineering and Technology (the IET),
DOI: 10.1049/el.2017.3873.
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