6 results on '"Deledalle, Charles-Alban"'
Search Results
2. Ratio-Based Multitemporal SAR Images Denoising: RABASAR.
- Author
-
Zhao, Weiying, Deledalle, Charles-Alban, Denis, Loic, Maitre, Henri, Nicolas, Jean-Marie, and Tupin, Florence
- Subjects
- *
IMAGE denoising , *SYNTHETIC aperture radar , *STRUCTURE-activity relationships , *FASTING , *TIME series analysis - Abstract
In this paper, we propose a fast and efficient multitemporal despeckling method. The key idea of the proposed approach is the use of the ratio image, provided by the ratio between an image and the temporal mean of the stack. This ratio image is easier to denoise than a single image thanks to its improved stationarity. Besides, temporally stable thin structures are well preserved thanks to the multitemporal mean. The proposed approach can be divided into three steps: 1) estimation of a “superimage” by temporal averaging and possibly spatial denoising; 2) denoising of the ratio between the noisy image of interest and the “superimage”; and 3) computation of the denoised image by remultiplying the denoised ratio by the “superimage.” Because of the improved spatial stationarity of the ratio images, denoising these ratio images with a speckle-reduction method is more effective than denoising images from the original multitemporal stack. The amount of data that is jointly processed is also reduced compared to other methods through the use of the “superimage” that sums up the temporal stack. The comparison with several state-of-the-art reference methods shows better results numerically (peak signal-noise-ratio and structure similarity index) as well as visually on simulated and synthetic aperture radar (SAR) time series. The proposed ratio-based denoising framework successfully extends single-image SAR denoising methods to time series by exploiting the persistence of many geometrical structures. [ABSTRACT FROM AUTHOR]
- Published
- 2019
- Full Text
- View/download PDF
3. Additional illustrations of NL-SAR method for resolution-preserving (Pol)(In)SAR denoising
- Author
-
DELEDALLE, Charles-Alban, DENIS, Loïc, TUPIN, Florence, REIGBER, Andreas, JÄGER, Marc, Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Laboratoire Hubert Curien [Saint Etienne] (LHC), Université Jean Monnet [Saint-Étienne] (UJM)-Centre National de la Recherche Scientifique (CNRS)-Institut d'Optique Graduate School (IOGS), Laboratoire Traitement et Communication de l'Information (LTCI), Télécom ParisTech-Institut Mines-Télécom [Paris] (IMT)-Centre National de la Recherche Scientifique (CNRS), Télécom ParisTech, DLR Microwaves and Radar Institute, German Aerospace Center (DLR), plafrim, labex PRIMES (ANR-11-LABX-0063), and CPU
- Subjects
Synthetic Aperture Radar (SAR) ,Interferometry ,Non-local means ,[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV] ,Polarimetry ,Estimation - Abstract
This document provides additional information and results of the method NL-SAR described in our paper: "NL-SAR: a unified Non-Local framework for resolution-preserving (Pol)(In)SAR denoising" submitted to IEEE Trans. on Geoscience and Remote Sensing [Deledalle et al., 2013]. NL-SAR is a fully automatic method for speckle reduction that handles amplitude, polarimetric and/or interferometric SAR data. It can process single look and multi-look images. The source code of the method is freely available at: http://www.math.u-bordeaux1.fr/cdeledal/nlsar.php.
- Published
- 2014
4. NL-SAR: A Unified Nonlocal Framework for Resolution-Preserving (Pol)(In)SAR Denoising.
- Author
-
Deledalle, Charles-Alban, Denis, Loïc, Tupin, Florence, Reigber, Andreas, and Jäger, Marc
- Subjects
- *
IMAGING systems , *SYNTHETIC aperture radar , *INTERFEROMETRY , *POLARIMETRY , *REMOTE sensing - Abstract
Speckle noise is an inherent problem in coherent imaging systems such as synthetic aperture radar. It creates strong intensity fluctuations and hampers the analysis of images and the estimation of local radiometric, polarimetric, or interferometric properties. Synthetic aperture radar (SAR) processing chains thus often include a multilooking (i.e., averaging) filter for speckle reduction, at the expense of a strong resolution loss. Preservation of point-like and fine structures and textures requires to adapt locally the estimation. Nonlocal (NL)-means successfully adapt smoothing by deriving data-driven weights from the similarity between small image patches. The generalization of nonlocal approaches offers a flexible framework for resolution-preserving speckle reduction. We describe a general method, i.e., NL-SAR, that builds extended nonlocal neighborhoods for denoising amplitude, polarimetric, and/or interferometric SAR images. These neighborhoods are defined on the basis of pixel similarity as evaluated by multichannel comparison of patches. Several nonlocal estimations are performed, and the best one is locally selected to form a single restored image with good preservation of radar structures and discontinuities. The proposed method is fully automatic and handles single and multilook images, with or without interferometric or polarimetric channels. Efficient speckle reduction with very good resolution preservation is demonstrated both on numerical experiments using simulated data, airborne, and spaceborne radar images. The source code of a parallel implementation of NL-SAR is released with this paper. [ABSTRACT FROM PUBLISHER]
- Published
- 2015
- Full Text
- View/download PDF
5. Two-Step Multitemporal Nonlocal Means for Synthetic Aperture Radar Images.
- Author
-
Xin Su, Deledalle, Charles-Alban, Tupin, Florence, and Hong Sun
- Subjects
- *
SYNTHETIC aperture radar , *IMAGING systems , *ESTIMATION theory , *INFORMATION storage & retrieval systems , *REDUNDANCY in engineering - Abstract
This paper presents a denoising approach for multitemporal synthetic aperture radar (SAR) images based on the concept of nonlocal means (NLM). It exploits the information redundancy existing in multitemporal images by a two-step strategy. The first step realizes a nonlocal weighted estimation driven by the redundancy in time, whereas the second step makes use of the nonlocal estimation in space. Using patch similarity miss-registration estimation, we also adapted this approach to the case of unregistered SAR images. The experiments illustrate the efficiency of the proposed method to denoise multitemporal images while preserving new information. [ABSTRACT FROM PUBLISHER]
- Published
- 2014
- Full Text
- View/download PDF
6. NL-InSAR: Nonlocal Interferogram Estimation.
- Author
-
Deledalle, Charles-Alban, Denis, Loïc, and Tupin, Florence
- Subjects
- *
SYNTHETIC aperture radar , *INTERFEROMETRY , *IMAGE reconstruction , *ESTIMATION theory , *REFLECTANCE , *IMAGING systems , *NOISE measurement , *PIXELS - Abstract
Interferometric synthetic aperture radar (SAR) data provide reflectivity, interferometric phase, and coherence images, which are paramount to scene interpretation or low-level processing tasks such as segmentation and 3-D reconstruction. These images are estimated in practice from a Hermitian product on local windows. These windows lead to biases and resolution losses due to the local heterogeneity caused by edges and textures. This paper proposes a nonlocal approach for the joint estimation of the reflectivity, the interferometric phase, and the coherence images from an interferometric pair of coregistered single-look complex (SLC) SAR images. Nonlocal techniques are known to efficiently reduce noise while preserving structures by performing the weighted averaging of similar pixels. Two pixels are considered similar if the surrounding image patches are “resembling.” Patch similarity is usually defined as the Euclidean distance between the vectors of graylevels. In this paper, a statistically grounded patch-similarity criterion suitable to SLC images is derived. A weighted maximum likelihood estimation of the SAR interferogram is then computed with weights derived in a data-driven way. Weights are defined from the intensity and interferometric phase and are iteratively refined based both on the similarity between noisy patches and on the similarity of patches from the previous estimate. The efficiency of this new interferogram construction technique is illustrated both qualitatively and quantitatively on synthetic and true data. [ABSTRACT FROM AUTHOR]
- Published
- 2011
- Full Text
- View/download PDF
Catalog
Discovery Service for Jio Institute Digital Library
For full access to our library's resources, please sign in.