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Content adaptive wavelet based method for joint denoising of depth and luminance images

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Abstract
In this paper we present a new method for joint denoising of depth and luminance images produced by time-of-flight camera. Here we assume that the sequence does not contain outlier points which can be present in the depth images. Our method first performs estimation of noise and signal covariance matrices and then performs vector denoising. Luminance image is segmented into similar contexts usina k-means algorithm, which are used for calculation of covariance matrices. Denoising results are compared with the ground truth images obtained by averaging of the multiple frames of the still scene.
Keywords
wavelets, depth images, noise estimation, denoising

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Chicago
Jovanov, Ljubomir, Nemanja Petrovic, Aleksandra Pizurica, and Wilfried Philips. 2007. “Content Adaptive Wavelet Based Method for Joint Denoising of Depth and Luminance Images.” In Proceedings of SPIE, the International Society for Optical Engineering, ed. F Truchelet and O Laligant. Vol. 6763. Bellingham, WA, USA: SPIE, the International Society for Optical Engineering.
APA
Jovanov, L., Petrovic, N., Pizurica, A., & Philips, W. (2007). Content adaptive wavelet based method for joint denoising of depth and luminance images. In F. Truchelet & O. Laligant (Eds.), Proceedings of SPIE, the International Society for Optical Engineering (Vol. 6763). Presented at the Conference on Wavelet Applications in Industrial Processing V, Bellingham, WA, USA: SPIE, the International Society for Optical Engineering.
Vancouver
1.
Jovanov L, Petrovic N, Pizurica A, Philips W. Content adaptive wavelet based method for joint denoising of depth and luminance images. In: Truchelet F, Laligant O, editors. Proceedings of SPIE, the International Society for Optical Engineering. Bellingham, WA, USA: SPIE, the International Society for Optical Engineering; 2007.
MLA
Jovanov, Ljubomir, Nemanja Petrovic, Aleksandra Pizurica, et al. “Content Adaptive Wavelet Based Method for Joint Denoising of Depth and Luminance Images.” Proceedings of SPIE, the International Society for Optical Engineering. Ed. F Truchelet & O Laligant. Vol. 6763. Bellingham, WA, USA: SPIE, the International Society for Optical Engineering, 2007. Print.
@inproceedings{424262,
  abstract     = {In this paper we present a new method for joint denoising of depth and luminance images produced by time-of-flight camera. Here we assume that the sequence does not contain outlier points which can be present in the depth images. Our method first performs estimation of noise and signal covariance matrices and then performs vector denoising. Luminance image is segmented into similar contexts usina k-means algorithm, which are used for calculation of covariance matrices. Denoising results are compared with the ground truth images obtained by averaging of the multiple frames of the still scene.},
  articleno    = {67630D},
  author       = {Jovanov, Ljubomir and Petrovic, Nemanja and Pizurica, Aleksandra and Philips, Wilfried},
  booktitle    = {Proceedings of SPIE, the International Society for Optical Engineering},
  editor       = {Truchelet, F and Laligant, O},
  issn         = {0277-786X},
  keyword      = {wavelets,depth images,noise estimation,denoising},
  language     = {eng},
  location     = {Boston, MA, USA},
  pages        = {8},
  publisher    = {SPIE, the International Society for Optical Engineering},
  title        = {Content adaptive wavelet based method for joint denoising of depth and luminance images},
  url          = {http://dx.doi.org/10.1117/12.736437},
  volume       = {6763},
  year         = {2007},
}

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