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Depth Upsampler Using Color and Depth Weight
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 Title & Authors
Depth Upsampler Using Color and Depth Weight
Shin, Soo-Yeon; Kim, Dong-Myung; Suh, Jae-Won;
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In this paper, we present an upsampling technique for depth map image using color and depth weights. First, we construct a high-resolution image using the bilinear interpolation technique. Next, we detect a common edge region using RGB color space, HSV color space, and depth image. If an interpolated pixel belongs to the common edge region, we calculate weighting values of color and depth in neighboring pixels and compute the cost value to determine the boundary pixel value. Finally, the pixel value having minimum cost is determined as the pixel value of the high-resolution depth image. Simulation results show that the proposed algorithm achieves good performance in terns of PSNR comparison and subjective visual quality.
3D;Depth Map;Upsampler;
 Cited by
S. B. Gokturk, H. Yalcin, and C. Bamji, "A Time-of-Flight Depth Sensor, System Description, Issues and Solutions," Proc. IEEE Conf. Computer Vision Pattern Recognition Workshops, p.35, 2004.

R. C. Gonzalez and R. E. Woods, Digital Image Processing, Prentice Hall, 2002.

J. Kopf, M. F. Cohen, D. Lischinski, and M. Uyttendaele, "Joint Bilateral Upsampling," ACM Trans. on Graphics, Vol.26, No.3, pp.1-6, 2010.

L. Yagguang, L. Zhang, and Y. Zhang, "Depth Map Super-resolution Via Iterative Joint-Trilateral-Upsampling," Proc. IEEE Conf. Visual Communications and Image Processing, pp.386-389, 2014.

Q. Yang, R. Yang, and James Davis, "Spatial-Depth Super Resolution for Rang Images," Proc. IEEE Conf. Computer Vision and Pattern Recognition, pp.1-8, 2007.

S. Y. Kim and Y. Ho, "Fast Edge-preserving Depth Image Upsampler," IEEE Trans. Consumer Electronics, Vol.21, No.32, pp.1176-1190, 2012.

J. T. Tou and R. C. Gonazalez, Pattern Recognition Principles, Addison-Wesley Publishing Company, 1974.

J. F. Canny, "A Computational Approach to Edge Detection," IEEE Trans. Pattern Analysis and Machine Intelligence, Vol.8, No.6, pp.679-698, 1986.

D. Scharstein and R. Szeliski, "A Taxonomy and Evaluation of Dense Two-Frame stereo Correspondence Algorithms," Proc. IEEE Conf. Stereo and Multi-Baseline Vision. Workshops, Vol.7, No.1, pp.7-42, 2002.