Paper
27 November 2002 Reconstruction of stereoscopic image using adaptive disparity estimation scheme
Author Affiliations +
Proceedings Volume 4864, Three-Dimensional TV, Video, and Display; (2002) https://doi.org/10.1117/12.454926
Event: ITCom 2002: The Convergence of Information Technologies and Communications, 2002, Boston, MA, United States
Abstract
In this paper, a new stereoscopic image reconstruction technique using an adaptive disparity estimation algorithm is proposed and its performance is analyzed in terms of PSNR through comparison to that of the conventional disparity estimation algorithms. In the proposed method, the feature-based disparity estimation method in which Canny mask operator is used for detecting the edge information from the input stereo pair are used for extracting the feature value. And, the matching window size for reconstruction of stereoscopic image is adaptively selected depending on the magnitude of the feature value of the input stereo pair by comparing with the predetermined threshold value. That is, coarse matching is carried out in the region having a small feature value while dense matching is carried out in the region having a large feature value. This new approach can not only reduce mismatching possibility of the disparity vector mostly happened in the conventional dense disparity estimation with a small matching window size, but also reduce the blocking effect occurred in the disparity estimation with a large matching window size. From some experimental results, it is found that the proposed algorithm improves PSNR of the reconstructed image about 5.36~7.76 dB on the average than that of the conventional algorithms.
© (2002) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kyung-Hoon Bae, Song-Taek Lim, Jung-Hwan Ko, and Eun-Soo Kim "Reconstruction of stereoscopic image using adaptive disparity estimation scheme", Proc. SPIE 4864, Three-Dimensional TV, Video, and Display, (27 November 2002); https://doi.org/10.1117/12.454926
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KEYWORDS
Reconstruction algorithms

Feature extraction

Image processing

3D image processing

Analytical research

Detection and tracking algorithms

Image restoration

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