A Fast Iterative Method for Removing Impulsive Noise From Sparse Signals
In this paper, we propose a new method to reconstruct a signal corrupted by noise where both signal and noise are sparse but in different domains. The main contribution of our algorithm is its low complexity; it has much lower run-time than most other algorithms. The reconstruction quality of our al...
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| Veröffentlicht in: | IEEE transactions on circuits and systems for video technology 2021-01, Vol.31 (1), p.38-48 |
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| container_title | IEEE transactions on circuits and systems for video technology |
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| creator | Sadrizadeh, Sahar Zarmehi, Nematollah Kangarshahi, Ehsan Asadi Abin, Hamidreza Marvasti, Farokh |
| description | In this paper, we propose a new method to reconstruct a signal corrupted by noise where both signal and noise are sparse but in different domains. The main contribution of our algorithm is its low complexity; it has much lower run-time than most other algorithms. The reconstruction quality of our algorithm is both objectively (in terms of PSNR and SSIM) and subjectively better or comparable to other state-of-the-art algorithms. We provide a cost function for our problem, present an iterative method to find its local minimum, and provide the analysis of the algorithm. As an application of this problem, we apply our algorithm for Salt-and-Pepper noise (SPN) and Random-Valued Impulsive Noise (RVIN) removal from images and compare our results with other notable algorithms in the literature. Furthermore, we apply our algorithm for removing clicks from audio signals. Simulation results show that our algorithms are simple and fast, and it outperforms other state-of-the-art methods in terms of reconstruction quality and/or complexity. |
| doi_str_mv | 10.1109/TCSVT.2020.2969563 |
| format | Article |
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| source | IEEE Electronic Library (IEL) |
| subjects | Adaptive thresholding Algorithms Audio signals Complexity Cost function Discrete cosine transforms image denoising Image reconstruction impulsive noise iterative method Iterative methods Mathematical model Noise Noise measurement Reconstruction sparse signal |
| title | A Fast Iterative Method for Removing Impulsive Noise From Sparse Signals |
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