Adaptive Thresholding for Sparse Image Reconstruction
The performance of the class of sparse reconstruction algorithms which is based on the iterative thresholding is highly dependent on a selection of the appropriate threshold value, controlling a trade-off between the algorithm execution time and the solution accuracy. This is why most of the state-o...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Telecommunications Society, Academic Mind
2023-07-01
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| Series: | Telfor Journal |
| Subjects: | |
| Online Access: | http://journal.telfor.rs/Published/Vol15No1/Vol15No1_A2.pdf |
| _version_ | 1797289875492306944 |
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| author | I. Volaric V. Sucic |
| author_facet | I. Volaric V. Sucic |
| author_sort | I. Volaric |
| collection | DOAJ |
| description | The performance of the class of sparse reconstruction algorithms which is based on the iterative thresholding is highly dependent on a selection of the appropriate threshold value, controlling a trade-off between the algorithm execution time and the solution accuracy. This is why most of the state-of-the-art reconstruction algorithms employ some method of decreasing the threshold value as the solution converges toward the optimal one. To address this problem we propose a data-driven adaptive threshold selection method based on the fast intersection of confidence intervals (FICI) method, with which we have augmented the two-step iterative shrinkage thresholding (TwIST) algorithm. The performance of the proposed algorithm, denoted as the FICI-TwIST algorithm, has been evaluated on a problem of image reconstruction with the missing pixels, exploiting image sparsity in the discrete cosine transformation domain. The obtained results have shown competitive performance in comparison with a number of state-of-the-art sparse reconstruction algorithms, even outperforming them in some scenarios. |
| first_indexed | 2024-03-07T19:12:20Z |
| format | Article |
| id | doaj.art-7b14a5fedfab4b2b80d4153c8f7059b5 |
| institution | Directory Open Access Journal |
| issn | 1821-3251 |
| language | English |
| last_indexed | 2024-03-07T19:12:20Z |
| publishDate | 2023-07-01 |
| publisher | Telecommunications Society, Academic Mind |
| record_format | Article |
| series | Telfor Journal |
| spelling | doaj.art-7b14a5fedfab4b2b80d4153c8f7059b52024-02-29T22:20:23ZengTelecommunications Society, Academic MindTelfor Journal1821-32512023-07-0115181310.5937/telfor2301008VAdaptive Thresholding for Sparse Image ReconstructionI. VolaricV. SucicThe performance of the class of sparse reconstruction algorithms which is based on the iterative thresholding is highly dependent on a selection of the appropriate threshold value, controlling a trade-off between the algorithm execution time and the solution accuracy. This is why most of the state-of-the-art reconstruction algorithms employ some method of decreasing the threshold value as the solution converges toward the optimal one. To address this problem we propose a data-driven adaptive threshold selection method based on the fast intersection of confidence intervals (FICI) method, with which we have augmented the two-step iterative shrinkage thresholding (TwIST) algorithm. The performance of the proposed algorithm, denoted as the FICI-TwIST algorithm, has been evaluated on a problem of image reconstruction with the missing pixels, exploiting image sparsity in the discrete cosine transformation domain. The obtained results have shown competitive performance in comparison with a number of state-of-the-art sparse reconstruction algorithms, even outperforming them in some scenarios.http://journal.telfor.rs/Published/Vol15No1/Vol15No1_A2.pdfcompressive sensingfast intersection of confidence intervals (fici) methodimage reconstructioniterative soft thresholdingsignal sparsitysparse reconstruction algorithm |
| spellingShingle | I. Volaric V. Sucic Adaptive Thresholding for Sparse Image Reconstruction Telfor Journal compressive sensing fast intersection of confidence intervals (fici) method image reconstruction iterative soft thresholding signal sparsity sparse reconstruction algorithm |
| title | Adaptive Thresholding for Sparse Image Reconstruction |
| title_full | Adaptive Thresholding for Sparse Image Reconstruction |
| title_fullStr | Adaptive Thresholding for Sparse Image Reconstruction |
| title_full_unstemmed | Adaptive Thresholding for Sparse Image Reconstruction |
| title_short | Adaptive Thresholding for Sparse Image Reconstruction |
| title_sort | adaptive thresholding for sparse image reconstruction |
| topic | compressive sensing fast intersection of confidence intervals (fici) method image reconstruction iterative soft thresholding signal sparsity sparse reconstruction algorithm |
| url | http://journal.telfor.rs/Published/Vol15No1/Vol15No1_A2.pdf |
| work_keys_str_mv | AT ivolaric adaptivethresholdingforsparseimagereconstruction AT vsucic adaptivethresholdingforsparseimagereconstruction |