Sparsity-Driven Despeckling for SAR Images

Küçük Resim Yok

Tarih

2016

Dergi Başlığı

Dergi ISSN

Cilt Başlığı

Yayıncı

Ieee-Inst Electrical Electronics Engineers Inc

Erişim Hakkı

info:eu-repo/semantics/closedAccess

Özet

Speckle noise inherent in synthetic aperture radar (SAR) images seriously affects the result of various SAR image processing tasks such as edge detection and segmentation. Thus, speckle reduction is critical and is used as a preprocessing step for smoothing homogeneous regions while preserving features such as edges and point scatterers. Although state-of-the-art methods provide better despeckling compared with conventional methods, their resource consumption is higher. In this letter, a sparsitydriven total-variation (TV) approach employing l0-norm, fractional norm, or l(1)-norm to smooth homogeneous regions with minimal degradation in edges and point scatterers is proposed. Proposed method, sparsity-driven despeckling (SDD), is capable of using different norms controlled by a single parameter and provides better or similar despeckling compared with the state-of-the-art methods with shorter execution times. Despeckling performance and execution time of the SDD are shown using synthetic and real-world SAR images.

Açıklama

Anahtar Kelimeler

Fractional norm, l(0)-norm, l(1)-norm, speckle reduction, synthetic aperture radar (SAR), total variation (TV)

Kaynak

Ieee Geoscience and Remote Sensing Letters

WoS Q Değeri

Q2

Scopus Q Değeri

Q1

Cilt

13

Sayı

1

Künye