Depth Mapping of Integral Images Through Viewpoint Image Extraction With a Hybrid Disparity Analysis Algorithm

Integral imaging is a technique capable of displaying 3D images with continuous parallax in full natural color. It is one of the most promising methods for producing smooth 3D images. Extracting depth information from integral image has various applications ranging from remote inspection, robotic vision, medical imaging, virtual reality, to content-based image coding and manipulation for integral imaging based 3D TV. This paper presents a method of generating a depth map from unidirectional integral images through viewpoint image extraction and using a hybrid disparity analysis algorithm combining multi-baseline, neighborhood constraint and relaxation strategies. It is shown that a depth map having few areas of uncertainty can be obtained from both computer and photographically generated integral images using this approach. The acceptable depth maps can be achieved from photographic captured integral images containing complicated object scene.

[1]  Jae-Hyeung Park,et al.  Novel depth extraction algorithm incorporating a lens array and a camera by reassembling pixel columns of elemental images , 2002, SPIE/COS Photonics Asia.

[2]  Sun-Yuan Kung,et al.  Hierarchical adaptive regularisation method for depth extraction from planar recording of 3D-integral images , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[3]  J Arai,et al.  Real-time pickup method for a three-dimensional image based on integral photography. , 1997, Applied optics.

[4]  Bahram Javidi,et al.  Digital three-dimensional image correlation by use of computer-reconstructed integral imaging. , 2002, Applied optics.

[5]  Sumio Yano,et al.  A study of visual fatigue and visual comfort for 3D HDTV/HDTV images , 2002 .

[6]  B. Javidi,et al.  Integral three-dimensional imaging with digital reconstruction. , 2001, Optics letters.

[7]  Bahram Javidi,et al.  Three-dimensional distortion-tolerant object recognition using integral imaging. , 2004, Optics express.

[8]  B. Javidi,et al.  Extended depth-of-field 3-D display and visualization by combination of amplitude-modulated microlenses and deconvolution tools , 2005, Journal of Display Technology.

[9]  Bahram Javidi,et al.  Improved resolution 3D object sensing and recognition using time multiplexed computational integral imaging. , 2003, Optics express.

[10]  Byoungho Lee,et al.  Depth extraction by use of a rectangular lens array and one-dimensional elemental image modification. , 2004, Applied optics.

[11]  Jeng-Sheng Huang,et al.  Stereo vision using a microcanonical mean field annealing neural network , 1997 .

[12]  Frederic Dufaux,et al.  Motion estimation techniques for digital TV: a review and a new contribution , 1995, Proc. IEEE.

[13]  Bahram Javidi,et al.  Formation of real, orthoscopic integral images by smart pixel mapping. , 2005, Optics express.

[14]  M. McCormick,et al.  Analytical model of a three-dimensional integral image recording system that uses circular- and hexagonal-based spherical surface microlenses. , 2001, Journal of the Optical Society of America. A, Optics, image science, and vision.

[15]  Amar Aggoun,et al.  Depth extraction from unidirectional integral image using a modified multibaseline technique , 2002, IS&T/SPIE Electronic Imaging.

[16]  T. Motoki,et al.  Present status of three-dimensional television research , 1995, Proc. IEEE.

[17]  Emanuele Trucco,et al.  Introductory techniques for 3-D computer vision , 1998 .

[18]  Bahram Javidi,et al.  Three-Dimensional Television, Video and Display Technology , 2002 .

[19]  Takeo Kanade,et al.  A Multiple-Baseline Stereo , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  Malcolm McCormick,et al.  Design and analysis of an image transfer system using microlens arrays , 1994 .

[21]  Takanori Okoshi.  Three-Dimensional Imaging Techniques , 1976 .

[22]  Takeo Kanade,et al.  A Stereo Matching Algorithm with an Adaptive Window: Theory and Experiment , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  Sun-Yuan Kung,et al.  A feature tracking algorithm using neighborhood relaxation with multi-candidate pre-screening , 1996, Proceedings of 3rd IEEE International Conference on Image Processing.