Image Denoising Using Nonlocal Means with Shape-Adaptive Patches and New Weights
Digital images captured from CMOS/CCD image sensors are prone to noise due to inherent electronic fluctuations and low photon count. To efficiently reduce the noise in the image, a novel image denoising strategy is proposed, which exploits both nonlocal self-similarity and local shape adaptation. Wi...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-01-01
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| Series: | Shock and Vibration |
| Online Access: | http://dx.doi.org/10.1155/2021/9532702 |
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| _version_ | 1832549197174276096 |
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| author | Chenglin Zuo Jun Ma Hao Xiong Lin Ran |
| author_facet | Chenglin Zuo Jun Ma Hao Xiong Lin Ran |
| author_sort | Chenglin Zuo |
| collection | DOAJ |
| description | Digital images captured from CMOS/CCD image sensors are prone to noise due to inherent electronic fluctuations and low photon count. To efficiently reduce the noise in the image, a novel image denoising strategy is proposed, which exploits both nonlocal self-similarity and local shape adaptation. With wavelet thresholding, the residual image in method noise, derived from the initial estimate using nonlocal means (NLM), is exploited further. By incorporating the role of both the initial estimate and the residual image, spatially adaptive patch shapes are defined, and new weights are calculated, which thus results in better denoising performance for NLM. Experimental results demonstrate that our proposed method significantly outperforms original NLM and achieves competitive denoising performance compared with state-of-the-art denoising methods. |
| format | Article |
| id | doaj-art-d3bbdf26a7044557842f92605aa23a15 |
| institution | Kabale University |
| issn | 1070-9622 1875-9203 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Shock and Vibration |
| spelling | doaj-art-d3bbdf26a7044557842f92605aa23a152025-02-03T06:12:06ZengWileyShock and Vibration1070-96221875-92032021-01-01202110.1155/2021/95327029532702Image Denoising Using Nonlocal Means with Shape-Adaptive Patches and New WeightsChenglin Zuo0Jun Ma1Hao Xiong2Lin Ran3Low Speed Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, ChinaLow Speed Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, ChinaLow Speed Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, ChinaLow Speed Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, ChinaDigital images captured from CMOS/CCD image sensors are prone to noise due to inherent electronic fluctuations and low photon count. To efficiently reduce the noise in the image, a novel image denoising strategy is proposed, which exploits both nonlocal self-similarity and local shape adaptation. With wavelet thresholding, the residual image in method noise, derived from the initial estimate using nonlocal means (NLM), is exploited further. By incorporating the role of both the initial estimate and the residual image, spatially adaptive patch shapes are defined, and new weights are calculated, which thus results in better denoising performance for NLM. Experimental results demonstrate that our proposed method significantly outperforms original NLM and achieves competitive denoising performance compared with state-of-the-art denoising methods.http://dx.doi.org/10.1155/2021/9532702 |
| spellingShingle | Chenglin Zuo Jun Ma Hao Xiong Lin Ran Image Denoising Using Nonlocal Means with Shape-Adaptive Patches and New Weights Shock and Vibration |
| title | Image Denoising Using Nonlocal Means with Shape-Adaptive Patches and New Weights |
| title_full | Image Denoising Using Nonlocal Means with Shape-Adaptive Patches and New Weights |
| title_fullStr | Image Denoising Using Nonlocal Means with Shape-Adaptive Patches and New Weights |
| title_full_unstemmed | Image Denoising Using Nonlocal Means with Shape-Adaptive Patches and New Weights |
| title_short | Image Denoising Using Nonlocal Means with Shape-Adaptive Patches and New Weights |
| title_sort | image denoising using nonlocal means with shape adaptive patches and new weights |
| url | http://dx.doi.org/10.1155/2021/9532702 |
| work_keys_str_mv | AT chenglinzuo imagedenoisingusingnonlocalmeanswithshapeadaptivepatchesandnewweights AT junma imagedenoisingusingnonlocalmeanswithshapeadaptivepatchesandnewweights AT haoxiong imagedenoisingusingnonlocalmeanswithshapeadaptivepatchesandnewweights AT linran imagedenoisingusingnonlocalmeanswithshapeadaptivepatchesandnewweights |