3D view image reconstruction in computational integral imaging using scale invariant feature transform and patch matching
Related Experiment Video
Updated: Jan 19, 2026

Detection and Quantification of Tunneling Nanotubes Using 3D Volume View Images
Published on: August 31, 2022
Abstract:
This paper realizes a computational integral imaging reconstruction method via scale invariant feature transform (SIFT) and patch matching to improve the visual quality of reconstructed 3D view images. To our knowledge, the 3D view images reconstructed from the elemental images suffer from artifacts, which leads to degradations in the visual quality. To prevent image degradation, in this paper, we use the correct regions obtained from the view images taken directly from the original object or use patch matching to replace the distorted regions. However, the initial matching regions could not meet our requirements owing to the limitations of the equipment and the inevitable shortcomings of the experimental operation. To solve these problems, we adopt SIFT descriptors and perspective transform to get the satisfying correct regions. We present the simulation and experimental results of the 3D view images and the evaluation of the quality of the corresponding images to test the performance of the proposed method. The simulation and experimental results indicate that the proposed method can significantly improve the visual quality of the 3D view images and verify the feasibility and effectiveness of the proposed method.
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