A two-stage blind image super-resolution algorithm based on kernel estimation

Yang Wang

doi:10.1117/12.3042022

10 September 2024 A two-stage blind image super-resolution algorithm based on kernel estimation

Yang Wang

Author Affiliations +

Proceedings Volume 13257, International Conference on Advanced Image Processing Technology (AIPT 2024); 1325707 (2024) https://doi.org/10.1117/12.3042022
Event: International Conference on Advanced Image Processing Technology (AIPT 2024), 2024, Chongqing, China

Abstract

Previous blind image super-resolution (BISR) approaches based on iterative methods tend to be relatively time-consuming and cause large amounts of computation, to address the problem, in this paper, we divide BISR into two stages: firstly, pre-kernels are pre-estimated and pre-SR images are pre-restored from LR images. After that, based on the features of different depths in the pre-SR network, we obtain the more accurate blur kernels, which help restore better SR images. We also improve the SR network with single way of fusion degradation by designing expert modules (EM) to deal with multiple degradation and spatial-channel fusion method to deepen the fusion of the degradation information and features.

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

Citation Download Citation

Yang Wang "A two-stage blind image super-resolution algorithm based on kernel estimation", Proc. SPIE 13257, International Conference on Advanced Image Processing Technology (AIPT 2024), 1325707 (10 September 2024); https://doi.org/10.1117/12.3042022

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KEYWORDS

Image fusion

Lawrencium

Feature fusion

Image restoration

Education and training

Super resolution

Convolution

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