24 November 2014 Image depth estimation from compressed sensing theory
Author Affiliations +
Proceedings Volume 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition; 930125 (2014) https://doi.org/10.1117/12.2072454
Event: International Symposium on Optoelectronic Technology and Application 2014, 2014, Beijing, China
Abstract
Depth information of the image is really necessary information to reconstruct a 3-dimensional object. The classical methods of depth estimation are generally divided into two categories: active and passive methods. The active methods requires the additional lighting equipment, passive methods also have a series of problems .They require a plurality of images obtained by capturing a plurality of viewpoints , and determine the locating occlusion boundary , etc., and hence the depth estimation has been a challenging problem in the research field of computer vision.1 Because of the depth information of the image has a natural sparse features, this paper uses a passive approach, the signal of sparse priori based on compressed sensing theory is used to estimate the depth of the image, without capturing multiple images, using a single input image can obtain a high quality depth map. Experimental results show that the depth map obtaining by our method, compared to the classical passive method, the contour sharpness, the depth of detail information and the robustness of noise are more advantages. The method also can be applied to re-focus the defocused images, and automatic scene segmentation and other issues, ultimately may have broad application prospects in the reconstruction of true 3-dimensional objects.
© (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Guangdong Du, Guangdong Du, Cheng Zhang, Cheng Zhang, Hong Cheng, Hong Cheng, Yan Liu, Yan Liu, Sui Wei, Sui Wei, } "Image depth estimation from compressed sensing theory", Proc. SPIE 9301, International Symposium on Optoelectronic Technology and Application 2014: Image Processing and Pattern Recognition, 930125 (24 November 2014); doi: 10.1117/12.2072454; https://doi.org/10.1117/12.2072454
PROCEEDINGS
9 PAGES


SHARE
RELATED CONTENT

Estimation of lens distortion correction from single images
Proceedings of SPIE (February 19 2014)
Reduced depth of field using multi-image fusion
Proceedings of SPIE (March 07 2013)
Rethinking camera user interfaces
Proceedings of SPIE (January 24 2012)
Real-time lucky imaging in FastCam project
Proceedings of SPIE (July 11 2008)

Back to Top