Super-resolution method for aligning face image based on residual back projection neural network

Abstract

The invention relates to a super-resolution method for aligning a face image based on a residual back projection neural network, and belongs to the technical field of image processing. A mode of combining iterative back projection and a deep learning neural network is adopted, and an ultralow-resolution face image is amplified by 8 times through three steps. The method comprises the following steps: (1) inputting an ultralow-resolution face image into a neural network, extracting depth features, and amplifying a low-resolution feature map to 128 * 128 by adopting a deconvolution network; (2) inputting the 128 * 128 feature map obtained in the step (1) into a residual back projection unit of a neural network, and obtaining a compensated 128 * 128 high-resolution feature map through continuous iteration; and (3) generating a final 128 * 128 high-resolution image through a convolution layer by using the high-resolution feature map obtained in the step (2). The method is clear in module and simple in step, and the super-resolution effect and efficiency meet the super-resolution requirement of the actual low-resolution face image.

Description

technical field [0001] The invention relates to a super-resolution method for aligning face images based on a residual back-projection neural network, and belongs to the technical field of image processing. [0002] technical background [0003] In the research field of computer vision, face image super-resolution has always been an important sub-topic. It not only has many practical application scenarios, but also is the basis of other research topics. [0004] From a practical point of view, many intelligent applications are inseparable from the support of face image super-resolution technology. The most important application is the urban surveillance system: with the rapid economic development, the video surveillance cameras around us are becoming more Many, these cameras are mainly used to build urban video surveillance systems, and play an important role in the criminal investigation business of public security organs. However, in the actual process of collecting faces ...

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to address the poor visual effect of existing aligned low-resolution face images, which are difficult to apply to existing face analysis systems. In order to enlarge ultra-low-resolution face images, a neural network alignment based on residual back projection is proposed Super-resolution methods for face images

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