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Optical Engineering

Ladar range image denoising by a nonlocal probability statistics algorithm
Author(s): Zhi-Wei Xia; Qi Li; Zhi-Peng Xiong; Qi Wang
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Paper Abstract

According to the characteristic of range images of coherent ladar and the basis of nonlocal means (NLM), a nonlocal probability statistics (NLPS) algorithm is proposed in this paper. The difference is that NLM performs denoising using the mean of the conditional probability distribution function (PDF) while NLPS using the maximum of the marginal PDF. In the algorithm, similar blocks are found out by the operation of block matching and form a group. Pixels in the group are analyzed by probability statistics and the gray value with maximum probability is used as the estimated value of the current pixel. The simulated range images of coherent ladar with different carrier-to-noise ratio and real range image of coherent ladar with 8 gray-scales are denoised by this algorithm, and the results are compared with those of median filter, multitemplate order mean filter, NLM, median nonlocal mean filter and its incorporation of anatomical side information, and unsupervised information-theoretic adaptive filter. The range abnormality noise and Gaussian noise in range image of coherent ladar are effectively suppressed by NLPS.

Paper Details

Date Published: 4 January 2013
PDF: 12 pages
Opt. Eng. 52(1) 017003 doi: 10.1117/1.OE.52.1.017003
Published in: Optical Engineering Volume 52, Issue 1
Show Author Affiliations
Zhi-Wei Xia, Harbin Institute of Technology (China)
Qi Li, Harbin Institute of Technology (China)
Zhi-Peng Xiong, Harbin Institute of Technology (China)
Qi Wang, Harbin Institute of Technology (China)


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