Title :
Building invariance properties for dictionaries of SAR image patches
Author :
Tabti, Sonia ; Deledalle, Charles-Alban ; Denis, Loic ; Tupin, Florence
Author_Institution :
Telecom ParisTech, LTCI, Inst. Mines-Telecom, Paris, France
Abstract :
Adding invariance properties to a dictionary-based model is a convenient way to reach a high representation capacity while maintaining a compact structure. Compact dictionaries of patches are desirable because they ease semantic interpretation of their elements (atoms) and offer robust decompositions even under strong speckle fluctuations. This paper describes how patches of a dictionary can be matched to a speckled image by accounting for unknown shifts and affine radio-metric changes. This procedure is used to build dictionaries of patches specific to SAR images. The dictionaries can then be used for denoising or classification purposes.
Keywords :
image classification; image denoising; image matching; radar imaging; synthetic aperture radar; SAR image patch dictionaries; affine radio-metric changes; building invariance properties; compact dictionaries; compact structure; dictionary-based model; image classification; image denoising; invariance properties; representation capacity; robust decompositions; semantic interpretation; speckle fluctuations; speckled image matching; Approximation error; Atomic measurements; Dictionaries; Equations; Noise measurement; Speckle; Patches; SAR images; contrast invariant; dictionary; shift-invariant;
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International
Conference_Location :
Quebec City, QC
DOI :
10.1109/IGARSS.2014.6947598