Ms. Qingyu Li Profile

Qingyu Li

at Jilin Univ

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Proceedings Article | 31 October 2016 Paper

A vertical parallax reduction method for stereoscopic video based on adaptive interpolation

Qingyu Li, Yan Zhao

Proceedings Volume 10020, 100201C (2016) https://doi.org/10.1117/12.2246479

KEYWORDS: Video, Visualization, Detection and tracking algorithms, Image scaling, 3D image processing, Cameras, Algorithms, Image interpolation, Edge detection, Image quality

Read Abstract +

The existence of vertical parallax is the main factor of affecting the viewing comfort of stereo video. Visual fatigue is gaining widespread attention with the booming development of 3D stereoscopic video technology. In order to reduce the vertical parallax without affecting the horizontal parallax, a self-adaptive image scaling algorithm is proposed, which can use the edge characteristics efficiently. In the meantime, the nonlinear Levenberg-Marquardt (L-M) algorithm is introduced in this paper to improve the accuracy of the transformation matrix. Firstly, the self-adaptive scaling algorithm is used for the original image interpolation. When the pixel point of original image is in the edge areas, the interpretation is implemented adaptively along the edge direction obtained by Sobel operator. Secondly the SIFT algorithm, which is invariant to scaling, rotation and affine transformation, is used to detect the feature matching points from the binocular images. Then according to the coordinate position of matching points, the transformation matrix, which can reduce the vertical parallax, is calculated using Levenberg-Marquardt algorithm. Finally, the transformation matrix is applied to target image to calculate the new coordinate position of each pixel from the view image. The experimental results show that: comparing with the method which reduces the vertical parallax using linear algorithm to calculate two-dimensional projective transformation, the proposed method improves the vertical parallax reduction obviously. At the same time, in terms of the impact on horizontal parallax, the proposed method has more similar horizontal parallax to that of the original image after vertical parallax reduction. Therefore, the proposed method can optimize the vertical parallax reduction.

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