Gaussian-Hermite moment-based depth estimation from single still image for stereo vision |
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| Affiliation: | 1. Department of Electrical and Electronic Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka 1205, Bangladesh;2. Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC 27606, USA;3. Department of Electrical and Computer Engineering, University of Toronto, Toronto, ON M5S 2E4, Canada;1. School of Information Engineering, Guangdong University of Technology, PR China;2. Fujian Provincial Key Laboratory of Data Mining and Applications, Fujian University of Technology, Fujian, PR China;1. Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116023, China;2. Operation Software and Simulation Institute, Dalian Navy Academy, Dalian 116018, China;1. Department of Mathematics, Shanghai Jiao Tong University, China;2. Department of Mathematics, Tongji University, China;3. Department of Mathematics, Hong Kong Baptist University, Hong Kong;1. College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China;2. Department of Information Management, Chaoyang University of Technology, Taichung, Taiwan;1. National Laboratory of Radar Signal Processing, Xidian University, Xi’an 710071, China;2. School of Computer Science and Technology, Xidian University, Xi’an 710071, China |
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| Abstract: | Depth information of objects plays a significant role in image-based rendering. Traditional depth estimation techniques use different visual cues including the disparity, motion, geometry, and defocus of objects. This paper presents a novel approach of focus cue-based depth estimation for still images using the Gaussian-Hermite moments (GHMs) of local neighboring pixels. The GHMs are chosen due to their superior reconstruction ability and invariance properties to intensity and geometric distortions of objects as compared to other moments. Since depths of local neighboring pixels are significantly correlated, the Laplacian matting is employed to obtain final depth map from the moment-based focus map. Experiments are conducted on images of indoor and outdoor scenes having objects with varying natures of resolution, edge, occlusion, and blur contents. Experimental results reveal that the depth estimated from GHMs can provide anaglyph images with stereo quality better than that provided by existing methods using traditional visual cues. |
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| Keywords: | Anaglyph image Depth estimation Focus cue Gaussian-Hermite moments Laplacian matting |
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