Open AccessSAR image despeckling using quadratic–linear approximated ℓ 1 ‐norm
Author(s) -
Nar Fatih
Publication year - 2018
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2017.3873
Subject(s) - synthetic aperture radar , smoothing , speckle noise , quadratic equation , speckle pattern , preprocessor , computation , noise reduction , norm (philosophy) , algorithm , computer science , artificial intelligence , computer vision , mathematics , geometry , political science , law
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 ℓ 1 ‐norm total variation regularisation 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.