Face super-resolution processing method and system based on high-frequency and low-frequency component fusion

Abstract

The invention discloses a face super-resolution processing method and system based on high-frequency and low-frequency component fusion. The method comprises the steps that S1, a multi-scale traininglibrary is constructed; S2, a to-be-processed low-resolution face image and an image in the training library into image blocks with overlapped parts are divided by adopting a same blocking mode; S3, apreprocessing module preprocesses a high-resolution face image library and a severe low-resolution face image library, and prepares a preprocessed neighbor relation for each library; S4, a low-frequency component determination module determines a low-frequency component for a to-be-processed low-resolution face image; S5, a high-frequency component determination module which takes a result of thelow-frequency component determination module as an input, determines a reconstructed image block through employing a neural network, and determines a high-frequency component for a to-be-processed low-resolution face image; and S6, the high-resolution face image blocks are spliced. The invention can remarkably improve the visual perception of restored images and is especially suitable for the restoration of face images in a low-quality monitoring environment.

Description

technical field [0001] The invention relates to the technical field of image processing and image restoration, in particular to a method and system for super-resolution processing of human faces with fusion of high and low frequency components. Background technique [0002] Face super-resolution technology is to learn the corresponding relationship between high and low resolution through the auxiliary training library, and then achieve the purpose of estimating high-resolution face images from existing low-resolution face images. Face super-resolution is now widely used in many fields, one of the most representative fields is face image enhancement in surveillance video. With the widespread popularization of surveillance systems, surveillance video is playing an increasingly important role in the process of criminal evidence collection and criminal investigation. Face images, as one of the direct evidence, occupy an important position in case analysis and court evidence col...

AI Technical Summary

Problems solved by technology

Therefore, although in the process of reconstructing low-quality images in general environments, good results can be obtained, but in the face of severe noise images represented by surveillance, the damage of high-frequency details has led to this kind of high-frequency details as the main consideration. The distance measurement criterion is no longer accurate, which seriously affects the accuracy of the local relationship description. Therefore, the subspace information of the image itself is easily damaged, and the image restored by traditional methods is not satisfactory.

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