Adaptive training library-based block domain face super-resolution reconstruction method

A super-resolution reconstruction and training library technology, applied in the field of image processing, can solve the problems of interfering super-resolution restoration results, unsatisfactory results, pixel destruction and aliasing, etc.

Active Publication Date: 2013-04-17
WUHAN UNIV
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Problems solved by technology

[0004] The face super-resolution problem is a problem with infinite solutions, because a low-quality image may correspond to many different high-quality images
Good results can be obtained when dealing with general face super-resolution problems, b

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  • Adaptive training library-based block domain face super-resolution reconstruction method
  • Adaptive training library-based block domain face super-resolution reconstruction method
  • Adaptive training library-based block domain face super-resolution reconstruction method

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Embodiment Construction

[0050] The block-domain face super-resolution method based on the self-adaptive training library provided by the present invention forms an self-adaptive training library for images block by block in a manifold-based framework, and screens the training information to obtain the most accurate correlation The highest training database information, thereby improving the objective quality and similarity of the recovery results. During specific implementation, computer software technology can be used to realize smooth automatic operation.

[0051] The present invention will be further described below with specific embodiments in conjunction with the accompanying drawings.

[0052] see figure 1 , the embodiment includes the following steps:

[0053] S1, obtain a high-resolution face image library Y s and the corresponding low-resolution face image library X s , high-resolution face image library Y s Align all high-resolution face images in position, low-resolution face image li...

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Abstract

The invention provides an adaptive training library-based block domain face super-resolution reconstruction method. The new method based on learning comprises the following steps of: firstly, uniformly dividing high resolution images and low resolution training images into blocks, and clustering in a block set for which position is considered as the unit; and then, adaptively selecting corresponding position training block set for each block of the input images, screening the adaptive training set according to neighboring selection and adaptive class selection, and recovering high frequency details in a low resolution block by executing principal component analysis coefficient projection in the adaptive training set. By the method, the problem of noise in super-resolution recovery of the face image (such as a monitoring image) with serious noise points is solved or relieved.

Description

technical field [0001] The invention relates to the field of image processing (mainly image restoration), and aims at the demand for face image restoration in low-quality surveillance video, and specifically relates to a block-domain face super-resolution reconstruction method based on an adaptive training library. Background technique [0002] In recent years, with the rapid development of security monitoring systems, monitoring and forensics has played an increasingly important role in the fields of security prevention and crime forensics, among which face image forensics is one of the important concerns of monitoring and forensics. However, due to the serious blur and noise caused by the long distance between the camera and the target face, bad weather (rain, fog, etc.), poor lighting conditions, etc. in the surveillance video, the usable pixels of the face image captured in the surveillance video are extremely low, and the image recovery , identification is often severel...

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Application Information

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IPC IPC(8): G06T5/50
Inventor 胡瑞敏陈亮韩镇沈亚君周治龙胡孟凌涂小萌夏洋卢涛江俊君
Owner WUHAN UNIV
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