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Fast video super-resolution reconstruction method based on reduced convolutional neural network

A super-resolution reconstruction and neural network technology, applied in the field of fast video super-resolution reconstruction, can solve the problems of insufficient calculation speed and reconstruction effect, and achieve the effect of optimizing reconstruction effect, increasing learning ability, and reducing the requirements of machine memory.

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

[0006] Although relevant research has achieved good video super-resolution reconstruction effects, there are still some deficiencies in computing speed and reconstruction effect.

Method used

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  • Fast video super-resolution reconstruction method based on reduced convolutional neural network
  • Fast video super-resolution reconstruction method based on reduced convolutional neural network
  • Fast video super-resolution reconstruction method based on reduced convolutional neural network

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Embodiment Construction

[0029] The invention will be further described below with reference to the accompanying drawings and in combination with specific embodiments, so that those skilled in the art can implement it by referring to the description, and the protection scope of the present invention is not limited to the specific embodiments.

[0030] The technical scheme adopted in the present invention is a fast video super-resolution reconstruction method based on a simplified convolutional neural network, comprising the following steps:

[0031] (1) Establish a network structure:

[0032] a. Take the current frame, the first two frames of the current frame, and the last two frames of the current frame, a total of five frames as the input of the system, expressed as X T , index T∈{t-2,t-1,t,t+1,t+2}, where t represents the current moment, and Y t Indicates the reconstructed current video frame;

[0033] b. Feature extraction and channel fusion: ①. First, filter the input volume X T Perform convo...

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Abstract

The invention relates to a fast video super-resolution reconstruction method based on a reduced convolutional neural network. Neighborhood information between video frames is utilized and the reconstruction speed is ensured. With consideration of the direct impact on the operation speed of the network by the input size, the provided method enables the pre-interpolation process of the traditional method to be removed; and features are extracted from a plurality of low-resolution input video frames directly and multi-dimensional feature channel fusion is carried out. A parametric linear correction unit is used as an activation function and a network structure is adjusted by using a small filter size to carry out multi-layer mapping, so that a phenomenon that important information of the video is lost because of the zero gradient in the network is avoided. And then a deconvolution layer is added at the end of the network to carry out upsampling, so that a reconstructed video. Meanwhile, with a network migration strategy, a reconstruction model under different scaling factors is realized quickly; and more high-frequency detail information is kept in the reconstructed video image and the reconstruction speed is increased.

Description

technical field [0001] The invention relates to the technical field of video super-resolution reconstruction, in particular to a fast video super-resolution reconstruction method based on a simplified convolutional neural network. Background technique [0002] In recent years, some high-definition video displays have developed rapidly, bringing users a series of good visual experiences, making video communication and entertainment one of the most promising services, such as Ultra High Definition (UHD) TV. At the same time, due to the limitations of video shooting equipment, most UHD resolution video content cannot be obtained directly. Therefore, it is necessary to perform super-resolution (Super-Resolution, LR) on the obtained low-resolution (Low-Resolution, LR) video SR) reconstruction to obtain high-resolution (High-Resolution, HR) video, so as to meet the growing needs of users, this technology has become one of the most active research fields in the world in recent year...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T3/40
CPCG06T3/4053G06T2207/10016G06T2207/20081
Inventor 蒋刚毅潘志勇郁梅谢登梅彭宗举陈芬邵华
Owner NINGBO UNIV
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