@InProceedings{7362800,
  author = {V. Bruni and D. Panella and D. Vitulano},
  booktitle = {2015 23rd European Signal Processing Conference (EUSIPCO)},
  title = {Non local means image denoising using noise-adaptive SSIM},
  year = {2015},
  pages = {2326-2330},
  abstract = {This paper embeds SSIM in place of the L2 norm in a one step Non Local Means (NLM) scheme. This is possible thanks to a new form of SSIM that can be formally derived from the classical SSIM using the spreading error analysis. This approach has several advantages over L2 norm based NLM such as greater robustness to parameters setting, higher performance in terms of PSNR and SSIM, optimal subjective visual quality. In addition, it is possible to show that the cascade of the proposed pure visual approach and a second step based on L2 norm allows us to reach results close (slightly less) to the state of the art (BM3D) in terms of PSNR and SSIM.},
  keywords = {error analysis;image denoising;optimal subjective visual quality;PSNR;spreading error analysis;NLM scheme;noise-adaptive SSIM;nonlocal mean image denoising;Noise reduction;Noise measurement;Visualization;Smoothing methods;Estimation;Europe;Signal processing;Image denoising;Non Local Means;SSIM;Wiener filter},
  doi = {10.1109/EUSIPCO.2015.7362800},
  issn = {2076-1465},
  month = {Aug},
  url = {https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570096817.pdf},
}

{"_id":"MGmsydem8NRw9vTuw","bibbaseid":"bruni-panella-vitulano-nonlocalmeansimagedenoisingusingnoiseadaptivessim-2015","authorIDs":[],"author_short":["Bruni, V.","Panella, D.","Vitulano, D."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","author":[{"firstnames":["V."],"propositions":[],"lastnames":["Bruni"],"suffixes":[]},{"firstnames":["D."],"propositions":[],"lastnames":["Panella"],"suffixes":[]},{"firstnames":["D."],"propositions":[],"lastnames":["Vitulano"],"suffixes":[]}],"booktitle":"2015 23rd European Signal Processing Conference (EUSIPCO)","title":"Non local means image denoising using noise-adaptive SSIM","year":"2015","pages":"2326-2330","abstract":"This paper embeds SSIM in place of the L2 norm in a one step Non Local Means (NLM) scheme. This is possible thanks to a new form of SSIM that can be formally derived from the classical SSIM using the spreading error analysis. This approach has several advantages over L2 norm based NLM such as greater robustness to parameters setting, higher performance in terms of PSNR and SSIM, optimal subjective visual quality. In addition, it is possible to show that the cascade of the proposed pure visual approach and a second step based on L2 norm allows us to reach results close (slightly less) to the state of the art (BM3D) in terms of PSNR and SSIM.","keywords":"error analysis;image denoising;optimal subjective visual quality;PSNR;spreading error analysis;NLM scheme;noise-adaptive SSIM;nonlocal mean image denoising;Noise reduction;Noise measurement;Visualization;Smoothing methods;Estimation;Europe;Signal processing;Image denoising;Non Local Means;SSIM;Wiener filter","doi":"10.1109/EUSIPCO.2015.7362800","issn":"2076-1465","month":"Aug","url":"https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570096817.pdf","bibtex":"@InProceedings{7362800,\n author = {V. Bruni and D. Panella and D. Vitulano},\n booktitle = {2015 23rd European Signal Processing Conference (EUSIPCO)},\n title = {Non local means image denoising using noise-adaptive SSIM},\n year = {2015},\n pages = {2326-2330},\n abstract = {This paper embeds SSIM in place of the L2 norm in a one step Non Local Means (NLM) scheme. This is possible thanks to a new form of SSIM that can be formally derived from the classical SSIM using the spreading error analysis. This approach has several advantages over L2 norm based NLM such as greater robustness to parameters setting, higher performance in terms of PSNR and SSIM, optimal subjective visual quality. In addition, it is possible to show that the cascade of the proposed pure visual approach and a second step based on L2 norm allows us to reach results close (slightly less) to the state of the art (BM3D) in terms of PSNR and SSIM.},\n keywords = {error analysis;image denoising;optimal subjective visual quality;PSNR;spreading error analysis;NLM scheme;noise-adaptive SSIM;nonlocal mean image denoising;Noise reduction;Noise measurement;Visualization;Smoothing methods;Estimation;Europe;Signal processing;Image denoising;Non Local Means;SSIM;Wiener filter},\n doi = {10.1109/EUSIPCO.2015.7362800},\n issn = {2076-1465},\n month = {Aug},\n url = {https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570096817.pdf},\n}\n\n","author_short":["Bruni, V.","Panella, D.","Vitulano, D."],"key":"7362800","id":"7362800","bibbaseid":"bruni-panella-vitulano-nonlocalmeansimagedenoisingusingnoiseadaptivessim-2015","role":"author","urls":{"Paper":"https://www.eurasip.org/proceedings/eusipco/eusipco2015/papers/1570096817.pdf"},"keyword":["error analysis;image denoising;optimal subjective visual quality;PSNR;spreading error analysis;NLM scheme;noise-adaptive SSIM;nonlocal mean image denoising;Noise reduction;Noise measurement;Visualization;Smoothing methods;Estimation;Europe;Signal processing;Image denoising;Non Local Means;SSIM;Wiener filter"],"metadata":{"authorlinks":{}},"downloads":0},"bibtype":"inproceedings","biburl":"https://raw.githubusercontent.com/Roznn/EUSIPCO/main/eusipco2015url.bib","creationDate":"2021-02-13T17:31:52.580Z","downloads":0,"keywords":["error analysis;image denoising;optimal subjective visual quality;psnr;spreading error analysis;nlm scheme;noise-adaptive ssim;nonlocal mean image denoising;noise reduction;noise measurement;visualization;smoothing methods;estimation;europe;signal processing;image denoising;non local means;ssim;wiener filter"],"search_terms":["non","local","means","image","denoising","using","noise","adaptive","ssim","bruni","panella","vitulano"],"title":"Non local means image denoising using noise-adaptive SSIM","year":2015,"dataSources":["eov4vbT6mnAiTpKji","knrZsDjSNHWtA9WNT"]}