Comparación de métodos para la detección de bordes en imágenes satélitales SAR
Date
2019
Journal Title
Journal ISSN
Volume Title
Publisher
Asociación Argentina de Mecánica Computacional
Abstract
Resumen. El reconocimiento y delimitación de regiones homogéneas en imágenes satelitates de ra- dar de apertura sintética (SAR) es un problema de interés por las diversas aplicaciones posibles. Sin embargo la presencia del ruido de speckle en la retrodispersión dificulta el procesamiento de las imá- genes con métodos tradicionales. Surge así el interés en el análisis y evaluación de distintas alternativas para superar esta dificultad. Presentamos en esta comunicación un análisis comparativo del desempe- ño de dos métodos desarrollados por uno de los autores con una nueva alternativa en desarrollo ba- sada en la divergencia de Jensen Shannon, una medida de semejanza entre distribuciones de probabi- lidad. Las densidades a comparar se estiman por el método del kernel de densidad. Se generan imá- genes sintéticas y se evalúa el desempeño de cada método por la cifra de mérito de Pratt (PFoM).
Abstract. The reconnaissance of homogeneous regions and the detection of the limit between them in synthetic aperture radar (SAR) satellite images is a subject of interest on account of numerous applica- tions. Nevertheless the presence of speckle noise in backscatter makes it difficult the images processing by traditional methods. Consequently it is of interest the analysis and evaluation of different alternatives to overcome this shortcoming. We present in this paper a comparative analysis of the performance of two methods developed by one of the authors with a new alternative in development based on Jensen Shannon divergence, a measure of similarity between two probability distributions. The probability den- sity functions to be compared are estimated by the kernel density approximation. Synthetic images are generated and the performance of the methods are evaluated by means of Pratt figure of merit.
Abstract. The reconnaissance of homogeneous regions and the detection of the limit between them in synthetic aperture radar (SAR) satellite images is a subject of interest on account of numerous applica- tions. Nevertheless the presence of speckle noise in backscatter makes it difficult the images processing by traditional methods. Consequently it is of interest the analysis and evaluation of different alternatives to overcome this shortcoming. We present in this paper a comparative analysis of the performance of two methods developed by one of the authors with a new alternative in development based on Jensen Shannon divergence, a measure of similarity between two probability distributions. The probability den- sity functions to be compared are estimated by the kernel density approximation. Synthetic images are generated and the performance of the methods are evaluated by means of Pratt figure of merit.
Description
Keywords
Speckle, SAR imágenes, Segmentación, SAR images, Segmentation
Citation
Mecánica computacional
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