Bilateral-circulation convolution network-based video super-resolution method and system

A two-way loop and convolutional network technology, applied in the field of video super-resolution methods and systems, can solve the problems of limiting the application range of multi-frame super-resolution technology, high computing costs, etc., and achieve the effect of improving the effect of video super-resolution

Active Publication Date: 2015-11-18
INST OF AUTOMATION CHINESE ACAD OF SCI
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Problems solved by technology

[0004] However, in practical applications, this modeling of temporal dependencies usually requires high c

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  • Bilateral-circulation convolution network-based video super-resolution method and system
  • Bilateral-circulation convolution network-based video super-resolution method and system
  • Bilateral-circulation convolution network-based video super-resolution method and system

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[0024] In order to make the object, technical solution and advantages of the present invention clearer, the present invention will be described in further detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0025] According to one aspect of the present invention, a video super-resolution method based on a bidirectional circular convolutional network is proposed, which can be widely applied to video super-resolution problems involving complex motion situations.

[0026] figure 1 It shows the flowchart of the video super-resolution method based on bidirectional circular convolutional network proposed by the present invention. figure 2 Shown is a bidirectional recurrent convolutional network structure used in an embodiment of the present invention.

[0027] Such as figure 1 Shown, described video super-resolution method based on two-way circular convolution network comprises the following steps:

[0028] Step 1. Establish a...

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Abstract

The invention discloses a bilateral-circulation convolution network-based video super-resolution method. The method comprises the steps as follows: establishing bilateral-circulation networks, comprising a forward circulation sub-network and a backward circulation sub-network according to time sequence, wherein each circulation sub-network comprises an input sequence layer, two implication sequence layers and an output sequence layer from the bottom to the top, and each sequence layer comprises a plurality of states corresponding to video frames in different moments; connecting these states by using three convolution operations, comprising a feed-forward convolution, a cyclic convolution and a condition convolution so as to obtain a bilateral-circulation convolution network; transmitting a trained video in the established bilateral-circulation convolution network, and using a stochastic gradient descent algorithm to minimize mean square error between a predicated high resolution video and an actual high resolution video so as to iteratively optimize the weight of the network, and obtain the final bilateral-circulation convolution network; and inputting low-resolution video sequence to be processed in a final bilateral-circulation convolution network mode to obtain a corresponding super-resolution result.

Description

technical field [0001] The invention relates to the fields of computer vision and machine learning, in particular to a video super-resolution method and system based on a bidirectional circular convolution network. Background technique [0002] With the emergence of a large number of high-definition playback devices in recent years, how to convert low-resolution video to high-resolution video that is more suitable for playback, that is, super-resolution technology, has gradually become a hot research issue in the field of computer vision. [0003] The current super-resolution work can be roughly divided into two categories: 1) single-image super-resolution, which assumes that all video frames are independent of each other, and then performs super-resolution on each video frame independently. This method ignores a very important feature in video sequences, that is, the temporal dependence between video frames. 2) Multi-frame super-resolution, this method takes into account t...

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Application Information

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IPC IPC(8): H04N7/01
Inventor 王亮王威黄岩
Owner INST OF AUTOMATION CHINESE ACAD OF SCI
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