Image super-resolution reconstruction algorithm based on jump connection residual network

Abstract

The invention relates to an image super-resolution reconstruction algorithm based on a jump connection residual network, and belongs to the technical field of image processing. The method comprises the steps of selecting a training data set, and performing bicubic interpolation on a low-resolution image; constructing a specific structure of the network, and formulating a network training strategy;performing detail extraction on the interpolated image; the dimension of the total feature is reduced, and the single-pixel receptive field is widened; performing multiple iterations on the network training until the maximum number of iterations is reached; and final high-resolution image reconstruction is completed in a global residual error learning mode. According to the method, the residual network based on jumping is combined with the sub-network based on the parallel channels, detail features of the shallow network are fully utilized, rapid learning of the detail features of the depth image is achieved, and rapid convergence of the network is achieved through adjustable gradient clipping.

Description

technical field [0001] The invention relates to an image super-resolution reconstruction algorithm based on a skip connection residual network, and belongs to the technical field of image processing. Background technique [0002] Super-resolution is to improve the resolution of the original image through hardware or software methods, and the process of obtaining a high-resolution image through a series of low-resolution images is super-resolution reconstruction. High-resolution images can provide more important details for digital image processing because of their high pixel density, and lay a good foundation for image post-processing. It has a wide range of application requirements in the fields of monitoring equipment, remote sensing images, medical imaging and facial recognition. However, due to limitations of imaging equipment, lighting and other conditions, the resolution of acquired images is often low. Therefore, how to effectively improve the quality of imaging ima...

AI Technical Summary

Problems solved by technology

[0007] The invention provides an image super-resolution reconstruction algorithm based on a skip connection residual network, which is used for the problem that the existing algorithm cannot make full use of the detailed features of the shallow network and obtains relatively little reconstruction information

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