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Image restoration method based on pixel recursion super-resolution model

A high-resolution image and super-resolution technology, which is applied in the field of image restoration based on the pixel-based recursive super-resolution model, can solve problems such as inability to restore images, and achieve the effect of improving resolution

Inactive Publication Date: 2017-07-18
SHENZHEN WEITESHI TECH
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Problems solved by technology

[0004] Aiming at the problem that the existing methods cannot restore images with insufficient details, an end-to-end trained pixel recursive super-resolution model is designed to improve the resolution while generating reasonable details, which can realize the restoration of low-resolution original images into High-resolution and detailed images

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  • Image restoration method based on pixel recursion super-resolution model
  • Image restoration method based on pixel recursion super-resolution model
  • Image restoration method based on pixel recursion super-resolution model

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[0042] It should be noted that, in the case of no conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present invention will be further described in detail below in conjunction with the drawings and specific embodiments.

[0043] figure 1 It is a system flowchart of a method for restoring an image based on a pixel recursive super-resolution model in the present invention. It mainly includes statistical correlation, super-resolution network, conditional network, prior network, and restored image.

[0044] Among them, the statistical correlation, let x and y denote low-resolution and high-resolution images, where y * represent real high-resolution images, in order to learn p θ The parametric model of (y|x), using low-resolution input corresponding to the large data set of real high-resolution output, expressed as Collecting a set of high-resolution images first, and then reducing their resolution as ne...

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Abstract

The invention provides an image restoration method based on a pixel recursion super-resolution model; the main contents include: statistics correlation, super resolution network, condition network, prior network, and recovery image; the method comprises the following steps: reasonably modeling the statistics correlation of high resolution image pixels so as to express multi-modal condition distribution according to low resolution input; using a PixelCNN framework to define strong prior on a natural image, and combining a depth adjusting convolution network to optimize the prior; finally outputting a vivid high resolution image; the method solves the difficulty that an image cannot be restored if original image details are insufficient, and designs the pixel recursion super-resolution model trained from end to end, thus improving resolution, forming reasonable details, and restoring the low resolution original image into a high resolution image with vivid details.

Description

technical field [0001] The invention relates to the field of image restoration, in particular to a method for restoring an image based on a pixel recursive super-resolution model. Background technique [0002] Image restoration is often used in astronomical observation, remote sensing and telemetry, biological science, medical imaging, traffic monitoring and other fields to eliminate non-ideal distortion. Specifically, in the field of medical imaging, it is applied to imaging systems such as X-ray and CT to suppress the noise of various medical imaging systems or image acquisition systems and improve the resolution of medical images. In the field of traffic monitoring, it can identify and identify blurred drivers, license plates, vehicles and other information in video surveillance. In addition, image restoration can also be used to identify blurred and faded text in library books, which is conducive to preserving culture. remains. Although there are many studies on improv...

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Application Information

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IPC IPC(8): G06T3/40G06N3/04G06N3/08
CPCG06N3/08G06T3/4076G06N3/045
Inventor 夏春秋
Owner SHENZHEN WEITESHI TECH
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