DocumentCode :
734181
Title :
Depth enhancement via non-local means filter
Author :
Ke Yang ; Yong Dou ; Xiaoyang Chen ; Shaohe Lv ; Peng Qiao
Author_Institution :
Nat. Univ. of Defense Technol., Changsha, China
fYear :
2015
fDate :
27-29 March 2015
Firstpage :
126
Lastpage :
130
Abstract :
The depth image captured by a RGB-D camera is noisy and usually misses the values at some pixels, especially around the object boundaries. There are many methods take advantage of the corresponding color images to enhance the depth images. Most of them bring the texture of the color image into the depth image. In this paper, an adaptive double non-local means (ADNLM) method of depth enhancement is proposed. First, ADNLM pre-inpaint the depth image via a color-guided non-local means method; second, a depth-based non-local means method is used to denoise the pre-inpainted depth image. Experiments on the public benchmarks show that, ADNLM can avoid the color texture, and effectively enhance the depth image, especially when there are several large missing regions in the depth image. Also, the performance in terms of PSNR of ADNLM is slightly better than that of the state of the arts.
Keywords :
cameras; image colour analysis; image denoising; image enhancement; image filtering; image texture; ADNLM method; PSNR; RGB-D camera; adaptive double nonlocal means method; color image texture; color-guided nonlocal means method; depth image enhancement; depth-based nonlocal means method; nonlocal mean filter; preinpainted depth image denoising; Adaptive filters; Filtering; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computational Intelligence (ICACI), 2015 Seventh International Conference on
Conference_Location :
Wuyi
Print_ISBN :
978-1-4799-7257-9
Type :
conf
DOI :
10.1109/ICACI.2015.7184762
Filename :
7184762
Link To Document :
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