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Video Image Hierarchical Reconstruction Method Based on Sparse Representation and Dictionary Learning

A technology of sparse representation and dictionary learning, which is applied in the field of super-resolution reconstruction of video images, can solve the problems of unsuitable video image reconstruction and long reconstruction time, and achieve long reconstruction time, minimum scope, and reduced reconstruction time. Effect

Active Publication Date: 2018-11-16
XIDIAN UNIV
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Problems solved by technology

Although this method can restore more detailed information, it usually requires a long reconstruction time to process the entire image area, and is not suitable for the reconstruction of video images containing multiple moving objects.

Method used

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  • Video Image Hierarchical Reconstruction Method Based on Sparse Representation and Dictionary Learning
  • Video Image Hierarchical Reconstruction Method Based on Sparse Representation and Dictionary Learning
  • Video Image Hierarchical Reconstruction Method Based on Sparse Representation and Dictionary Learning

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Embodiment Construction

[0022] specific implementation plan

[0023] Attached below figure 1 The steps of the present invention are further described in detail:

[0024] Step 1. Get a sample set.

[0025] The image collection provided by the PASCAL VOC committee is used as a sample database, which includes 20 categories of human beings, animals, vehicles and indoors: among them, animals include birds, cats, cows, dogs, horses, and sheep; vehicles include Airplane, bicycle, boat, bus, car, motorcycle, train; indoor including bottle, chair, dining table, potted plant, sofa, TV.

[0026] 10 images are randomly selected in each directory, and 200 sample images are obtained. Use the obtained 200 sample images to form a high-resolution sample set The obtained 200 sample images are respectively down-sampled by 3 times to obtain 200 low-resolution images, and these 200 low-resolution images are used to form a low-resolution sample set High Resolution Sample Set I h and low-resolution sample set I l ...

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Abstract

The invention discloses a sparse representation and dictionary learning-based video image layered reconstruction method. The main objective of the invention is to solve the problem of long consumed time in video image reconstruction in the prior art. The method includes the following steps of: (1) obtaining a sample set; (2) layering images in the sample set; (3) training the images of the sample set before and after layering so as to obtain high-resolution dictionaries and low-resolution dictionaries of the sample set before and after layering; (4) dividing an image to be reconstructed into a main region, a sub region or a region-of-non-interest; (5) reconstructing the main region according to the high-resolution dictionaries and the low-resolution dictionaries of the sample set after layering; reconstructing the sub region according to the high-resolution dictionaries and the low-resolution dictionaries of the sample set before layering; (7) reconstructing the region-of-non-interest; (8) fusing a reconstructed main region and a reconstructed sub region into a reconstructed region-of-non-interest so as to obtain a complete reconstructed image. With the method of the invention adopted, the reconstruction time of the image is reduced. The method can be used for the processing of medical images, natural images and remote sensing images.

Description

technical field [0001] The invention belongs to the technical field of video and image processing, and relates to a super-resolution reconstruction method of video images, which can be used in medical images, natural images, remote sensing images and other occasions that generally require high-resolution images. Background technique [0002] Due to the limitation of the inherent properties of the imaging system and the influence of many factors such as atmospheric interference, the obtained single image or video will have problems such as poor imaging quality and low resolution. How to restore its original appearance or improve its resolution, clarity and other quality indicators based on the existing hardware conditions and acquired video images has always been a hot issue in video image scientific research and engineering applications. Super-resolution reconstruction is a technology that can effectively improve and increase the resolution level of video images. It reconstr...

Claims

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Application Information

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IPC IPC(8): G06T5/50G06K9/62
Inventor 王海王柯刘岩张皓迪李彬毛敏泉
Owner XIDIAN UNIV
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