Exploitation of the additive component of the polarimetric noise model for speckle filtering

Ratio filters for speckle noise reduction in SAR imagery are recursive filters where the image structure is iteratively recovered from an initial oversmoothed image. We show that the MBPolSAR filter could be interepreted as a ratio filter applied to the off-diagonal terms of the covariance/coherency matix. From this observation, we propose a new polarimetric ratio filter allowing us to recover the image structure from all the terms of the covariance matrix. In addition, we briefly look at how the additive noise component could also be exploited for the image structure extraction. Filtering results on both simulated and real PolSAR images are shown.Peer ReviewedPostprint (published version

Optimum graph cuts for pruning binary partition trees of polarimetric SAR images

This paper investigates several optimum graph-cut techniques for pruning binary partition trees (BPTs) and their usefulness for the low-level processing of polarimetric synthetic aperture radar (PolSAR) images. BPTs group pixels to form homogeneous regions, which are hierarchically structured by inclusion in a binary tree. They provide multiple resolutions of description and easy access to subsets of regions. Once constructed, BPTs can be used for a large number of applications. Many of these applications consist in populating the tree with a specific feature and in applying a graph cut called pruning to extract a partition of the space. In this paper, different pruning examples involving the optimization of a global criterion are discussed and analyzed in the context of PolSAR images for segmentation. Through the objective evaluation of the resulting partitions by means of precision-and-recall-for-boundaries curves, the best pruning technique is identified, and the influence of the tree construction on the performances is assessed.Peer ReviewedPostprint (author's final draft

On the extension of multidimensional speckle noise model from single-look to multilook SAR imagery

Speckle noise represents one of the major problems when synthetic aperture radar (SAR) data are considered. Despite the fact that speckle is caused by the scattering process itself, it must be considered as a noise source due to the complexity of the scattering process. The presence of speckle makes data interpretation difficult, but it also affects the quantitative retrieval of physical parameters. In the case of one-dimensional SAR systems, speckle is completely determined by a multiplicative noise component. Nevertheless, for multidimensional SAR systems, speckle results from the combination of multiplicative and additive noise components. This model has been first developed for single-look data. The objective of this paper is to extend the single-look data model to define a multilook multidimensional speckle noise model. The asymptotic analysis of this extension, for a large number of averaged samples, is also considered to assess the model properties. Details and validation of the multilook multidimensional speckle noise model are provided both theoretically and by means of experimental SAR data acquired by the experimental synthetic aperture radar system, operated by the German Aerospace Center.Peer Reviewe

Image Restoration for Remote Sensing: Overview and Toolbox

Remote sensing provides valuable information about objects or areas from a distance in either active (e.g., RADAR and LiDAR) or passive (e.g., multispectral and hyperspectral) modes. The quality of data acquired by remotely sensed imaging sensors (both active and passive) is often degraded by a variety of noise types and artifacts. Image restoration, which is a vibrant field of research in the remote sensing community, is the task of recovering the true unknown image from the degraded observed image. Each imaging sensor induces unique noise types and artifacts into the observed image. This fact has led to the expansion of restoration techniques in different paths according to each sensor type. This review paper brings together the advances of image restoration techniques with particular focuses on synthetic aperture radar and hyperspectral images as the most active sub-fields of image restoration in the remote sensing community. We, therefore, provide a comprehensive, discipline-specific starting point for researchers at different levels (i.e., students, researchers, and senior researchers) willing to investigate the vibrant topic of data restoration by supplying sufficient detail and references. Additionally, this review paper accompanies a toolbox to provide a platform to encourage interested students and researchers in the field to further explore the restoration techniques and fast-forward the community. The toolboxes are provided in https://github.com/ImageRestorationToolbox.Comment: This paper is under review in GRS

Classification of Pre-Filtered Multichannel Remote Sensing Images

Open acces: http://www.intechopen.com/books/remote-sensing-advanced-techniques-and-platforms/classification-of-pre-filtered-multichanel-rs-imagesInternational audienc

Multidimensional SAR data representation and processing based on Binary Partition Trees

English: A novel multidimensional SAR data abstraction is presented, based on Binary Partition Trees (BPT). This data abstraction is employed for different applications, as data filtering and segmentation, change detection, etc. The BPT can be contructed from a Polarimetric SAR (PolSAR) image or from a serie of coregistered acquisitions, conforming a tool that enables the systematic exploitation of PolSAR datasets simultaneously in the space and time dimensions.Castellano: na nueva abstracción de datos SAR multidimensionales es presentada, basada en Árboles de Partición Binaria (BPT). Esta abstracción de datos se emplea para distintas aplicaciones, como filtrado, segmentación, detección de cambios, etc. El BPT puede construirse a partir de una imagen SAR polarimétrica o de una serie temporal de imágenes, siendo una herramienta que permite la explotación sistemática de sets de datos PolSAR simultáneamente en espacio y tiempo.Català: Una nova abstracció de dades SAR multidimensionals és presentada, basada en Arbres de Partició Binària (BPT). Aquesta abstracció de dades s'empra per a diferents aplicacions, com filtrat, segmentació, detecció de canvis, etc. El BPT es pot construir a partir d'una imatge SAR polarimètrica o d'una sèrie temporal d'imatges, sent una eina que permet l'explotació sistemàtica de sets de dades PolSAR simultàniament en espai i temps

Statistical assessment of eigenvector-based target decomposition theorems in radar polarimetry

© 2005 IEEE.Carlos López-Martínez, Eric Pottier and Shane R. Cloud

Dynamical Approach for Real-Time Monitoring of Agricultural Crops

In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.This work was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) and EU FEDER under Project TEC2011-28201-C02-02 and in part by the Generalitat Valenciana under Project ACOMP/2014/136

Edge enhancement algorithm based on the wavelet transform for automatic edge detection in SAR images

This paper presents a novel technique for automatic edge enhancement and detection in synthetic aperture radar (SAR) images. The characteristics of SAR images justify the importance of an edge enhancement step prior to edge detection. Therefore, this paper presents a robust and unsupervised edge enhancement algorithm based on a combination of wavelet coefficients at different scales. The performance of the method is first tested on simulated images. Then, in order to complete the automatic detection chain, among the different options for the decision stage, the use of geodesic active contour is proposed. The second part of this paper suggests the extraction of the coastline in SAR images as a particular case of edge detection. Hence, after highlighting its practical interest, the technique that is theoretically presented in the first part of this paper is applied to real scenarios. Finally, the chances of its operational capability are assessed.Peer ReviewedPostprint (published version