Image super-resolution method based on feature correlation, storage medium and terminal equipment

Abstract

The invention discloses an image super-resolution method based on feature correlation, a storage medium and terminal equipment, the image super-resolution method applies a preset super-resolution network, and the super-resolution network comprises a feature extraction module, a residual block attention module and an image reconstruction module; the method comprises the following steps: inputting alow-resolution image into a feature extraction module, and outputting a shallow feature map through the feature extraction module; inputting the shallow feature map into a residual block attention module, and performing spatial and channel feature correlation learning through the residual block attention module to obtain a depth feature map; and inputting the depth feature map into an image reconstruction module, and outputting a high-resolution image through the image reconstruction module. According to the invention, spatial and channel feature correlation learning is carried out on the feature image through the residual block attention module, and the expression capability of the feature image is enhanced, so that the super-resolution effect of the image is improved.

Description

technical field [0001] The invention relates to the technical field of artificial intelligence, in particular to an image super-resolution method based on feature correlation, a storage medium and a terminal device. Background technique [0002] Image resolution is an important indicator to measure image quality. The higher the resolution, the finer the details, the better the quality, and the richer the information contained in the image. Therefore, images with higher resolution have important application value and research prospects in various computer vision tasks, such as military security, satellite monitoring, traffic supervision, criminal investigation and other applications. However, due to cost issues, the image acquisition, storage, and transmission processes in actual situations will inevitably be limited by external conditions or other interferences, resulting in varying degrees of quality degradation. [0003] Super-resolution is a technology to improve the res...

AI Technical Summary

Problems solved by technology

However, the deeper and wider convolutional neural network increases the difficulty, and at the same time ignores the correlation between features, which makes the processing effect a bottleneck

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