A face super-resolution processing method and system based on a context linear model
A linear model and super-resolution technology, applied in image data processing, instruments, graphics and image conversion, etc., can solve problems such as unsatisfactory effects, pixel destruction and aliasing, and easy damage to image subspace information
Inactive Publication Date: 2018-12-14
WUHAN UNIV
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However, when the image quality is very low, the pixels will be severely damaged and aliased, and the subspace information of the image itself will be easily damaged. The image restored by traditional methods is not satisfactory.
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[0046] In order to facilitate those of ordinary skill in the art to understand and implement the present invention, the present invention will be described in further detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the implementation examples described here are only used to illustrate and explain the present invention, and are not intended to limit this invention.
[0047] The present invention uses the manifold space of the image block in the library as the second-layer manifold, uses the manifold space of the image block to be processed as the first manifold, and provides the consistency of multiple expressions of the image block to be processed through the spatial association of the manifold space To enhance the accurate representation and robustness of image patches with consistency constraints. The present invention introduces a double-layer manifold assumption into the face super-resolution algorithm based on the t...
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The invention discloses a face super-resolution processing method and system based on a context linear model. The method comprises steps of: constructing a training database; dividing a low-resolution face image to be processed and an image in the training database into image blocks with overlapped portions by using the same partitioning way; constructing adjacent block spaces of the low-resolution face image blocks to be processed one by one; helping to estimating corresponding high-resolution blocks by using each adjacent block of the block at a target position so as to derive a high-resolution block set; determining a weight coefficient in a low-resolution database by computing a relation between target blocks and adjacent blocks in the low-resolution image to be processed and a relation between target blocks and adjacent blocks in the low-resolution image in the training database; fusing the high-resolution estimated set into a high-resolution estimated block; and finally splicing the high-resolution face image block. The method and the system may obviously restore the visual feeling of the images, and are especially suitable for the restoration of face images under a low-quality monitoring environment.
Description
technical field [0001] The invention belongs to the technical field of image processing and image restoration, and in particular relates to a face super-resolution processing method and system based on context linear model constraints. 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 collection. ...
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IPC IPC(8): G06T3/40
CPCG06T3/4053
Inventor 胡瑞敏陈亮周楚李青杨庆雄卢正马芸韩镇魏雪丽丁新渠慎明
Owner WUHAN UNIV