{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T02:07:41Z","timestamp":1760148461747,"version":"build-2065373602"},"reference-count":29,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2023,5,8]],"date-time":"2023-05-08T00:00:00Z","timestamp":1683504000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Conselho Nacional de Desenvolvimento Cient\u00edfico e Tecnol\u00f3gico (CNPq)","award":["200725\/2022-0","410695"],"award-info":[{"award-number":["200725\/2022-0","410695"]}]},{"name":"Victoria University of Wellington","award":["200725\/2022-0","410695"],"award-info":[{"award-number":["200725\/2022-0","410695"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Edge detection is one of the most critical operations for moving from data to information. Finding edges between objects is relevant for image understanding, classification, segmentation, and change detection, among other applications. The Gambini Algorithm is a good choice for finding evidence of edges. It finds the point at which a function of the difference of properties is maximized. This algorithm is very general and accepts many types of objective functions. We use an objective function built with likelihoods. Imaging with active microwave sensors has a revolutionary role in remote sensing. This technology has the potential to provide high-resolution images regardless of the Sun\u2019s illumination and almost independently of the atmospheric conditions. Images from PolSAR sensors are sensitive to the target\u2019s dielectric properties and structures in several polarization states of the electromagnetic waves. Edge detection in polarimetric synthetic-aperture radar (PolSAR) imagery is challenging because of the low signal-to-noise ratio and the data format (complex matrices). There are several known marginal models stemming from the complex Wishart model for the full complex format. Each of these models renders a different likelihood. This work generalizes previous studies by incorporating the ratio of intensities as evidence for edge detection. We discuss solutions for the often challenging problem of parameter estimation. We propose a technique which rejects edge estimates built with thin evidence. Using this idea of discarding potentially irrelevant evidence, we propose a technique for fusing edge pieces of evidence from different channels that only incorporate those likely to contribute positively. We use this approach for both edge and change detection in single- and multilook images from three different sensors.<\/jats:p>","DOI":"10.3390\/rs15092479","type":"journal-article","created":{"date-parts":[[2023,5,9]],"date-time":"2023-05-09T01:06:28Z","timestamp":1683594388000},"page":"2479","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Feature Selection for Edge Detection in PolSAR Images"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8479-9128","authenticated-orcid":false,"given":"Anderson A.","family":"De Borba","sequence":"first","affiliation":[{"name":"Department of Computing and Informatics (FCI\u2013BigMAAp), Mackenzie Presbyterian University (UPM), S\u00e3o Paulo 01221-040, Brazil"},{"name":"School of Mathematics and Statistics, Victoria University of Wellington, Wellington 6021, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8947-8865","authenticated-orcid":false,"given":"Arnab","family":"Muhuri","sequence":"additional","affiliation":[{"name":"Earth Observation and Modelling (EOM), Geographisches Institut, Christian-Albrechts-Universit\u00e4t zu Kiel, 24118 Schleswig-Holstein, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6830-1067","authenticated-orcid":false,"given":"Mauricio","family":"Marengoni","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Computer Science, Albion College, Albion, MI 49224, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8002-5341","authenticated-orcid":false,"given":"Alejandro C.","family":"Frery","sequence":"additional","affiliation":[{"name":"School of Mathematics and Statistics, Victoria University of Wellington, Wellington 6021, New Zealand"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,5,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Blake, A., and Isard, M. (1998). Active Contours, Springer.","DOI":"10.1007\/978-1-4471-1555-7"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Szeliski, R. (2022). Computer Vision: Algorithms and Applications, Springer. [2nd ed.].","DOI":"10.1007\/978-3-030-34372-9"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"5037","DOI":"10.1080\/01431160600702616","article-title":"Feature Extraction in Speckled Imagery using Dynamic B-Spline Deformable Contours under the G0 Model","volume":"27","author":"Gambini","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"15","DOI":"10.1007\/s11222-007-9034-y","article-title":"Accuracy of Edge Detection Methods with Local Information in Speckled Imagery","volume":"18","author":"Gambini","year":"2008","journal-title":"Stat. Comput."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1007\/s11045-010-0113-4","article-title":"Polarimetric SAR Image Segmentation with B-Splines and a New Statistical Model","volume":"21","author":"Frery","year":"2010","journal-title":"Multidimens. Syst. Signal Process."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"648","DOI":"10.1109\/JSTARS.2013.2266319","article-title":"Comparing Edge Detection Methods Based on Stochastic Entropies and Distances for PolSAR Imagery","volume":"7","author":"Nascimento","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"987","DOI":"10.1109\/JSTARS.2017.2647846","article-title":"The Geodesic Distance between GI0 Models and its Application to Region Discrimination","volume":"10","author":"Gambini","year":"2017","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2182","DOI":"10.1016\/j.matcom.2012.04.013","article-title":"Nonparametric edge detection in speckled imagery","volume":"82","author":"Frery","year":"2012","journal-title":"Math. Comput. Simul."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2020.3022511","article-title":"Fusion of Evidences in Intensities Channels for Edge Detection in PolSAR Images","volume":"19","author":"Borba","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Rey, A., Revollo Sarmiento, N., Frery, A.C., and Delrieux, C. (2022). Automatic Delineation of Water Bodies in SAR Images with a Novel Stochastic Distance Approach. Remote Sens., 14.","DOI":"10.3390\/rs14225716"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1007\/s12145-019-00380-5","article-title":"Change detection techniques for remote sensing applications: A survey","volume":"12","author":"Asokan","year":"2019","journal-title":"Earth Sci. Informatics"},{"key":"ref_12","first-page":"1","article-title":"Change Detection in Multilook Polarimetric SAR Imagery with Determinant Ratio Test Statistic","volume":"60","author":"Bouhlel","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"764","DOI":"10.1109\/36.7708","article-title":"A statistical and geometrical edge detector for SAR images","volume":"26","author":"Touzi","year":"1988","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"20","DOI":"10.1109\/TGRS.2002.808063","article-title":"CFAR edge detector for polarimetric SAR images","volume":"41","author":"Schou","year":"2003","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_15","unstructured":"Chapman, B., and Shi., J. (2004). CLPX-Airborne: Airborne Synthetic Aperture Radar (AIRSAR) Imagery, Version 1 [Data Set], NASA National Snow and Ice Data Center Distributed Active Archive Center."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Bouhlel, N., Akbari, V., and M\u00e9ric, S. (2021). Change Detection in Multilook Polarimetric SAR Imagery with DRT Statistic. IEEE Dataport.","DOI":"10.1109\/TGRS.2020.3043517"},{"key":"ref_17","unstructured":"Nobre, R., Rodrigues, A., Rosa, R., Medeiros, F., Feitosa, R., Estev\u00e3o, A., and Barros, A. (2017). GRSS SAR\/PolSAR Database. IEEE Dataport."},{"key":"ref_18","unstructured":"Long, D.G., and Ulaby, F.T. (2014). Microwave Radar and Radiometric Remote Sensing, The University of Michigan Press."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"152","DOI":"10.1214\/aoms\/1177704250","article-title":"Statistical Analysis Based on a Certain Complex Gaussian Distribution (an Introduction)","volume":"34","author":"Goodman","year":"1963","journal-title":"Ann. Math. Stat."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1017","DOI":"10.1109\/36.312890","article-title":"Intensity and phase statistics of multilook polarimetric and interferometric SAR imagery","volume":"32","author":"Lee","year":"1994","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1016\/j.jmva.2005.05.014","article-title":"A trivariate chi-squared distribution derived from the complex Wishart distribution","volume":"97","author":"Hagedorn","year":"2006","journal-title":"J. Multivar. Anal."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Ferreira, J.A., Nascimento, A.D.C., and Frery, A.C. (2022). PolSAR Models with Multimodal Intensities. Remote Sens., 14.","DOI":"10.3390\/rs14205083"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Feng, Y., Wen, M., Zhang, J., Ji, F., and Ning, G. (2016, January 15\u201318). Sum of arbitrarily correlated Gamma random variables with unequal parameters and its application in wireless communications. Proceedings of the 2016 International Conference on Computing, Networking and Communications (ICNC), Kauai, HI, USA.","DOI":"10.1109\/ICCNC.2016.7440693"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1007\/s00180-010-0217-1","article-title":"maxLik: A package for maximum likelihood estimation in R","volume":"26","author":"Henningsen","year":"2011","journal-title":"Comput. Stat."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"13","DOI":"10.32614\/RJ-2013-002","article-title":"Generalized Simulated Annealing for Global Optimization: The GenSA Package","volume":"5","author":"Xiang","year":"2013","journal-title":"R J."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1186\/1687-6180-2011-28","article-title":"Optimal edge detection using multiple operators for image understanding","volume":"2011","author":"Giannarou","year":"2011","journal-title":"EURASIP J. Adv. Signal Process."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"338","DOI":"10.14429\/dsj.58.1653","article-title":"Pixel-level Image Fusion using Wavelets and Principal Component Analysis","volume":"58","author":"Naidu","year":"2008","journal-title":"Def. Sci. J."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Mitchell, H. (2010). Image Fusion: Theories, Techniques and Applications, Springer.","DOI":"10.1007\/978-3-642-11216-4"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2153","DOI":"10.1109\/TPAMI.2015.2408351","article-title":"An Efficient Algorithm for Calculating the Exact Hausdorff Distance","volume":"37","author":"Taha","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/9\/2479\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T19:31:38Z","timestamp":1760124698000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/9\/2479"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,8]]},"references-count":29,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2023,5]]}},"alternative-id":["rs15092479"],"URL":"https:\/\/doi.org\/10.3390\/rs15092479","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2023,5,8]]}}}