{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,21]],"date-time":"2026-04-21T15:09:27Z","timestamp":1776784167711,"version":"3.51.2"},"reference-count":30,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2021,4,22]],"date-time":"2021-04-22T00:00:00Z","timestamp":1619049600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Sparse signal processing has been used in synthetic aperture radar (SAR) imaging due to the maturity of compressed sensing theory. As a typical sparse reconstruction method, L1 regularization generally causes bias effects as well as ignoring region-based features. Our team has proposed to linearly combine the nonconvex penalty and the total variation (TV)-norm penalty as a compound regularizer in the imaging model, called nonconvex and TV regularization, which can not only reduce the bias caused by L1 regularization but also enhance point-based and region-based features. In this paper, we use the variable splitting scheme and modify the alternating direction method of multipliers (ADMM), generating a novel algorithm to solve the above optimization problem. Moreover, we analyze the radiometric properties of sparse-signal-processing-based SAR imaging results and introduce three indexes suitable for sparse SAR imaging for quantitative evaluation. In experiments, we process the Gaofen-3 (GF-3) data utilizing the proposed method, and quantitatively evaluate the reconstructed SAR image quality. Experimental results and image quality analysis verify the effectiveness of the proposed method in improving the reconstruction accuracy and the radiometric resolution without sacrificing the spatial resolution.<\/jats:p>","DOI":"10.3390\/rs13091643","type":"journal-article","created":{"date-parts":[[2021,4,22]],"date-time":"2021-04-22T21:25:56Z","timestamp":1619126756000},"page":"1643","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":19,"title":["Sparse SAR Imaging and Quantitative Evaluation Based on Nonconvex and TV Regularization"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3338-2482","authenticated-orcid":false,"given":"Zhongqiu","family":"Xu","sequence":"first","affiliation":[{"name":"Key Laboratory of Spatial Information Processing and Application System Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bingchen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Laboratory of Spatial Information Processing and Application System Technology, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guoru","family":"Zhou","sequence":"additional","affiliation":[{"name":"Key Laboratory of Spatial Information Processing and Application System Technology, Chinese Academy of Sciences, Beijing 100190, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lihua","family":"Zhong","sequence":"additional","affiliation":[{"name":"Key Laboratory of Spatial Information Processing and Application System Technology, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yirong","family":"Wu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Spatial Information Processing and Application System Technology, Chinese Academy of Sciences, Beijing 100190, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1402","DOI":"10.1016\/j.sigpro.2009.11.009","article-title":"On compressive sensing applied to radar","volume":"90","author":"Ender","year":"2010","journal-title":"Signal Process."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1722","DOI":"10.1007\/s11432-012-4633-4","article-title":"Sparse microwave imaging: Principles and applications","volume":"55","author":"Zhang","year":"2012","journal-title":"Sci. China Inf. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1109\/MSP.2014.2312834","article-title":"Sparsity-driven synthetic aperture radar imaging: Reconstruction, autofocusing, moving targets, and compressed sensing","volume":"31","author":"Cetin","year":"2014","journal-title":"IEEE Signal Process. Mag."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Ao, D., Wang, R., Hu, C., and Li, Y. (2017). A Sparse SAR Imaging Method Based on Multiple Measurement Vectors Model. Remote Sens., 9.","DOI":"10.3390\/rs9030297"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"3748","DOI":"10.1109\/TGRS.2017.2679129","article-title":"Extended Chirp Scaling-Baseband Azimuth Scaling-Based Azimuth-Range Decouple L1 Regularization for TOPS SAR Imaging via CAMP","volume":"55","author":"Bi","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Baraniuk, R., and Steeghs, P. (2007, January 17\u201320). Compressive radar imaging. Proceedings of the 2007 IEEE Radar Conference, Waltham, MA, USA.","DOI":"10.1109\/RADAR.2007.374203"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"4285","DOI":"10.1109\/TGRS.2010.2051231","article-title":"A novel strategy for radar imaging based on compressive sensing","volume":"48","author":"Alonso","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1109\/JSTSP.2009.2039181","article-title":"Compressed synthetic aperture radar","volume":"4","author":"Patel","year":"2010","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1016\/j.acha.2016.01.002","article-title":"Sparse recovery via differential inclusions","volume":"41","author":"Osher","year":"2016","journal-title":"Appl. Comput. Harmon. Anal."},{"key":"ref_10","first-page":"2313","article-title":"The Dantzig selector: Statistical estimation when p is much larger than n","volume":"35","author":"Candes","year":"2007","journal-title":"Ann. Stat."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1109\/TCI.2016.2580498","article-title":"An augmented lagrangian method for complex-valued compressed sar imaging","volume":"2","author":"Cetin","year":"2016","journal-title":"IEEE Trans. Comput. Imaging"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4481","DOI":"10.1109\/TSP.2017.2711501","article-title":"Sparse regularization via convex analysis","volume":"65","author":"Selesnick","year":"2017","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s11432-018-9464-4","article-title":"A SAR imaging method based on generalized minimax-concave penalty","volume":"62","author":"Wei","year":"2019","journal-title":"Sci. China Inf. Sci."},{"key":"ref_14","unstructured":"Gong, P., Zhang, C., Lu, Z., Huang, J., and Ye, J. (2013, January 16\u201321). A general iterative shrinkage and thresholding algorithm for non-convex regularized optimization problems. Proceedings of the International Conference on Machine Learning, Atlanta, GA, USA."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"923","DOI":"10.1016\/j.dsp.2012.07.011","article-title":"SAR image reconstruction and autofocus by compressed sensing","volume":"22","year":"2012","journal-title":"Digit. Signal Process."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"2765","DOI":"10.1109\/TGRS.2014.2364525","article-title":"Adaptive total variation regularization based SAR image despeckling and despeckling evaluation index","volume":"53","author":"Zhao","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"5529","DOI":"10.1109\/JSEN.2019.2904611","article-title":"Compressive sensing based SAR imaging and autofocus using improved Tikhonov regularization","volume":"19","author":"Kang","year":"2019","journal-title":"IEEE Sens. J."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"350","DOI":"10.1109\/JSTARS.2020.3034431","article-title":"An Accurate Sparse SAR Imaging Method for Enhancing Region-Based Features Via Nonconvex and TV Regularization","volume":"14","author":"Xu","year":"2021","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Miao, W., Lin, Z., Gao, H., and Shi, S. (2018). Millimeter-Wave InSAR Image Reconstruction Approach by Total Variation Regularized Matrix Completion. Remote Sens., 10.","DOI":"10.3390\/rs10071053"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2345","DOI":"10.1109\/TIP.2010.2047910","article-title":"Fast Image Recovery Using Variable Splitting and Constrained Optimization","volume":"19","author":"Afonso","year":"2010","journal-title":"IEEE Trans. Image Process."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"681","DOI":"10.1109\/TIP.2010.2076294","article-title":"An Augmented Lagrangian Approach to the Constrained Optimization Formulation of Imaging Inverse Problems","volume":"20","author":"Afonso","year":"2011","journal-title":"IEEE Trans. Image Process."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.1109\/LGRS.2018.2821238","article-title":"A preliminary evaluation of the GaoFen-3 SAR radiation characteristics in land surface and compared with Radarsat-2 and Sentinel-1A","volume":"15","author":"Chen","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"660","DOI":"10.1109\/TGRS.2009.2026742","article-title":"TerraSAR-X system performance characterization and verification","volume":"48","author":"Mittermayer","year":"2009","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","unstructured":"Oliver, C., and Quegan, S. (2004). Understanding Synthetic Aperture Radar Images, SciTech Publishing."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Cozzolino, D., Verdoliva, L., Scarpa, G., and Poggi, G. (2020). Nonlocal CNN SAR Image Despeckling. Remote Sens., 12.","DOI":"10.3390\/rs12061006"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1023\/B:JMIV.0000011321.19549.88","article-title":"An algorithm for total variation minimization and applications","volume":"20","author":"Chambolle","year":"2004","journal-title":"J. Math. Imaging Vis."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"352","DOI":"10.1109\/JSTARS.2013.2263309","article-title":"Fast compressed sensing SAR imaging based on approximated observation","volume":"7","author":"Fang","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1006","DOI":"10.1109\/JPROC.2009.2037526","article-title":"Sparsity and compressed sensing in radar imaging","volume":"98","author":"Potter","year":"2010","journal-title":"Proc. IEEE"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"313","DOI":"10.1080\/02757259409532206","article-title":"Speckle filtering of synthetic aperture radar images: A review","volume":"8","author":"Lee","year":"1994","journal-title":"Remote Sens. Rev."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"786","DOI":"10.1109\/36.298008","article-title":"Precision SAR processing using chirp scaling","volume":"32","author":"Raney","year":"1994","journal-title":"IEEE Trans. Geosci. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1643\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:51:30Z","timestamp":1760161890000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/9\/1643"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,22]]},"references-count":30,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13091643"],"URL":"https:\/\/doi.org\/10.3390\/rs13091643","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,22]]}}}