{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:27:03Z","timestamp":1760146023294,"version":"build-2065373602"},"reference-count":21,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T00:00:00Z","timestamp":1726790400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Shengli Geophysical Research Institute of Sinopec","award":["P22021"],"award-info":[{"award-number":["P22021"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The utilization of the inversion-based algorithm for spectral decomposition using constrained least-squares spectral analysis (CLSSA) facilitates a time\u2013frequency spectrum with higher temporal and frequency resolution. The conventional CLSSA algorithm is solved by optimizing an L2-norm regularized least-squares misfit function using Gaussian elimination, which suffers from intensive computational cost. Instead of solving an L2-norm regularized misfit function, we propose to use an L1-norm regularized objective function to enhance the sparsity of the resulting time\u2013frequency spectra. Then, we utilize a faster, smarter, and greedier algorithm named greedy-FISTA to enhance the computational efficiency. Compared to the short-time Fourier transform, continuous wavelet transform, and the conventional CLSSA method, the sparsity-enhanced CLSSA with the greedy-FISTA is capable of achieving time\u2013frequency spectra with higher resolution but with much less computational cost. The applicability of this sparsity-enhanced CLSSA method is demonstrated through synthetic and real data examples.<\/jats:p>","DOI":"10.3390\/rs16183486","type":"journal-article","created":{"date-parts":[[2024,9,20]],"date-time":"2024-09-20T04:31:23Z","timestamp":1726806683000},"page":"3486","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Sparsity-Enhanced Constrained Least-Squares Spectral Analysis with Greedy-FISTA"],"prefix":"10.3390","volume":"16","author":[{"given":"Guohua","family":"Wei","sequence":"first","affiliation":[{"name":"School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China"},{"name":"Shengli Geophysical Research Institute of Sinopec, Dongying 257000, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7672-7949","authenticated-orcid":false,"given":"Wubing","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China"}]},{"given":"Zhenchun","family":"Li","sequence":"additional","affiliation":[{"name":"School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8692-8405","authenticated-orcid":false,"given":"Li-Yun","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,9,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"1041","DOI":"10.1190\/1.1440994","article-title":"Complex seismic trace analysis","volume":"44","author":"Taner","year":"1979","journal-title":"Geophysics"},{"key":"ref_2","first-page":"353","article-title":"Interpretational applications of spectral decomposition in reservoir characterization","volume":"18","author":"Partyka","year":"1999","journal-title":"Geophysics"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"120","DOI":"10.1190\/1.1559038","article-title":"Instantaneous spectral analysis: Detection of low-frequency shadows associated with hydrocarbons","volume":"22","author":"Castagna","year":"2003","journal-title":"Lead. 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