Single image re-enhancement method based on detail compensation network

A single image, detailed technology, applied in the field of image processing, can solve the problem of limited information, achieve the effect of improving the effect and good supplementary ability

Pending Publication Date: 2020-05-15
HANGZHOU DIANZI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

For the above reasons, the enhancement method of a single image is more attractive and easier to implement in practical applications, but due to the limited amount of information in a single image, the recovery of image details is a major challenge

Method used

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  • Single image re-enhancement method based on detail compensation network
  • Single image re-enhancement method based on detail compensation network
  • Single image re-enhancement method based on detail compensation network

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Embodiment Construction

[0026] The present invention will be further described below in conjunction with drawings and embodiments.

[0027] This embodiment includes the following steps:

[0028] 1. Image decomposition. For the obtained data set, the image decomposition operation is required. According to the Retinex theory, the image can be divided into high-frequency components and low-frequency components.

[0029] I(x,y)=I L (x,y)+I R (x,y) (1)

[0030] where I represents the original image, I L Indicates the low-frequency components of the image, I R Represents the high-frequency components of the image. (x, y) in the formula represents the coordinate position of the pixel in the image.

[0031] The decomposition part of the image is to obtain the low-frequency part of the image by first performing low-pass filtering on the image, and then subtract the original image from the low-frequency component of the obtained image to obtain the high-frequency component of the image. The low-pass fi...

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Abstract

The invention relates to a single image re-enhancement method based on a detail compensation network. According to the method, an image is decomposed, high-frequency components in the image are extracted, and then image details in the image are learned by utilizing the strong learning capability of the convolutional network. The method can make full use of the expression capability of a convolution layer for local spatial correlation and high-dimensional features. In order to train the model more fully, data enhancement is adopted. Finally, image detail compensation is made on the image enhanced by the traditional method. The method provided by the invention has relatively strong image detail supplementing capability, and the image enhancement effect is improved.

Description

technical field [0001] The invention belongs to the field of image processing, and relates to a single image re-enhancement method based on a detail compensation network. Background technique [0002] Reproducing natural scenes with good contrast, vivid colors, and rich details is a fundamental goal of digital photography. However, the acquired images suffer from low contrast due to poor lighting conditions and the limited dynamic range of the imaging device. The resulting low-contrast and low-quality images not only degrade human perception, but the performance of many computer vision and image analysis algorithms may also be affected. Therefore, contrast enhancement is very important as an important means to improve the quality of recorded images and make the details of images clearer. [0003] Traditional single-image contrast enhancement techniques include histogram-based algorithms and Retinex-based algorithms. Histogram-based methods enhance the contrast of images b...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06T5/00G06T5/40
CPCG06T5/007G06T5/009G06T5/40G06T2207/20081G06T2207/20084
Inventor 文成林沈硕郑乐军沈平旭
Owner HANGZHOU DIANZI UNIV
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