Image super-resolution reconstruction based on NEDI constraints

Xinxin Chen; Huiquan Wang

doi:10.1117/12.3030749

5 June 2024 Image super-resolution reconstruction based on NEDI constraints

Xinxin Chen, Huiquan Wang

Proceedings Volume 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024); 131635L (2024) https://doi.org/10.1117/12.3030749
Event: International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 2024, Xi'an, China

Abstract

The classical NEDI algorithm causes covariance parity distortion among multiple original images due to the different structures of reference pixel points in the covariance estimation window, resulting in edge artifacts and blurring phenomena in the reconstructed images. The solutions of optimal window selection and transforming the edge consistency constraints into a priori conditions are proposed to address this problem and are experimentally verified in single-frame image reconstruction and sequence image reconstruction. The experimental results show that the algorithm in this paper solves the problems of jumping points and blurring at the edges of the reconstructed image caused by the classical NEDI algorithm's pairwise distortion, and has a better visual effect.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Xinxin Chen and Huiquan Wang "Image super-resolution reconstruction based on NEDI constraints", Proc. SPIE 13163, Fourth International Conference on Mechanical, Electronics, and Electrical and Automation Control (METMS 2024), 131635L (5 June 2024); https://doi.org/10.1117/12.3030749

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