{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,1]],"date-time":"2025-12-01T15:47:06Z","timestamp":1764604026263,"version":"build-2065373602"},"reference-count":23,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2024,1,24]],"date-time":"2024-01-24T00:00:00Z","timestamp":1706054400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"University of Rijeka","award":["UNIRI-TEHNIC-18-67"],"award-info":[{"award-number":["UNIRI-TEHNIC-18-67"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>One of the frequently used classes of sparse reconstruction algorithms is based on the iterative shrinkage\/thresholding procedure, in which the thresholding parameter controls a trade-off between the algorithm\u2019s accuracy and execution time. In order to avoid this trade-off, we propose using a fast intersection of confidence intervals method in order to adaptively control the threshold value throughout the iterations of the reconstruction algorithm. We have upgraded the two-step iterative shrinkage thresholding algorithm with a such procedure, improving its performance. The proposed algorithm, denoted as the FICI-TwIST, along with a few selected state-of-the-art sparse reconstruction algorithms, has been tested on the classical problem of image recovery by emphasizing the image sparsity in the discrete cosine and the discrete wavelet domain. Furthermore, we have derived a single wavelet transformation matrix which avoids wrapping effects, thereby achieving significantly faster execution times as compared to a more traditional function-based transformation. The obtained results indicate the competitive performance of the proposed algorithm, even in cases where all algorithm parameters have been individually fine-tuned for best performance.<\/jats:p>","DOI":"10.3390\/info15020071","type":"journal-article","created":{"date-parts":[[2024,1,24]],"date-time":"2024-01-24T09:57:42Z","timestamp":1706090262000},"page":"71","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["A Fast Intersection of Confidence Intervals Method-Based Adaptive Thresholding for Sparse Image Reconstruction Using the Matrix Form of the Wavelet Transform"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2400-0633","authenticated-orcid":false,"given":"Ivan","family":"Volaric","sequence":"first","affiliation":[{"name":"Faculty of Engineering, University of Rijeka, HR-51000 Rijeka, Croatia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5345-4706","authenticated-orcid":false,"given":"Victor","family":"Sucic","sequence":"additional","affiliation":[{"name":"Faculty of Engineering, University of Rijeka, HR-51000 Rijeka, Croatia"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Stankovi\u0107, S., Orovi\u0107, I., and Sejdi\u0107, E. 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