Title :
Sparse Representations for Range Data Restoration
Author :
Mahmoudi, Mona ; Sapiro, Guillermo
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Minnesota, Minneapolis, MN, USA
fDate :
5/1/2012 12:00:00 AM
Abstract :
In this paper, the problem of denoising and occlusion restoration of 3-D range data based on dictionary learning and sparse representation methods is explored. We apply these techniques after converting the noisy 3-D surface into one or more images. We present experimental results on the proposed approaches.
Keywords :
image denoising; image registration; learning (artificial intelligence); denoising problem; dictionary learning; image restoration; occlusion restoration; range data restoration; sparse representations; Dictionaries; Image resolution; Image restoration; Noise; Noise measurement; Shape; Three dimensional displays; Occlusion restoration; range data denoising; range data resolution enhancement; sparse modeling; Algorithms; Image Enhancement; Image Interpretation, Computer-Assisted; Imaging, Three-Dimensional; Information Storage and Retrieval; Pattern Recognition, Automated; Reproducibility of Results; Sensitivity and Specificity;
Journal_Title :
Image Processing, IEEE Transactions on
DOI :
10.1109/TIP.2012.2185940
