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An Image Dehazing Method Based on Derivative Graph Fusion Strategy

A technology derived from images and images, applied in image enhancement, image data processing, biological neural network models, etc., can solve the problems of incomplete dehazing and local color cast, and achieve good dehazing effect, high fidelity, enhanced The effect of contrast

Active Publication Date: 2021-04-20
CENT SOUTH UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The problem to be solved by the present invention is to provide an image defogging method based on a derivative map fusion strategy in view of the existing defogging method relying on the transmission map and the atmospheric value prediction mechanism, which has problems such as incomplete defogging and local color shift. It can effectively extract the derivative image of the foggy image from multiple angles through the fusion of the defogging network, thereby realizing image defogging, and has a good defogging effect on images of various fog concentrations in various scenes

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  • An Image Dehazing Method Based on Derivative Graph Fusion Strategy
  • An Image Dehazing Method Based on Derivative Graph Fusion Strategy
  • An Image Dehazing Method Based on Derivative Graph Fusion Strategy

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Embodiment 1

[0093] This embodiment is aimed at any image containing fog, and the overall implementation process is as follows figure 1 As shown, the dehazing result is generated according to the following steps:

[0094] Step A: Construct a sample set with a large number of original foggy images and their corresponding fog-free images;

[0095] Step B: Extract the following five derivative images from the original foggy image from the five angles of improving the details of the distant view and the near view, eliminating the image color cast caused by atmospheric light, enhancing the brightness of the image, and enhancing the contrast of the image:

[0096] 1) Exposure map I EM

[0097] First, the original foggy image I hazy ( image 3 (a)) is converted to HIS color space by RGB color space, obtains its hue (H), saturation (S) and brightness (I) component map;

[0098] Then, the exposure evaluation map EM is calculated from the brightness component map I according to the following fo...

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Abstract

The invention discloses an image defogging method based on a derivative graph fusion strategy, which includes the following steps: Step A: Construct a sample set based on a large number of original foggy images and their corresponding fog-free images; Extract the derivative image of the original foggy image from two angles to enhance the detail recovery of the image's distant and near scenes by the dehazing method, eliminate color cast and enhance contrast; step C: build a U-shaped convolutional neural network; step D: cascade step A to obtain Derivative map of the original foggy image and the original foggy image are used as input, and the haze-free image is used as the output to train the network built by step C; Step E: use the network trained by step D, and concatenate the original foggy image and the derivative map corresponding to the foggy image as input Predict haze-free images after dehazing. The invention has good defogging effect.

Description

technical field [0001] The invention belongs to the field of image information processing, and in particular relates to an image defogging method based on a derivative graph fusion strategy. Background technique [0002] Image dehazing aims to recover the details of a scene and estimate an unknown haze-free image from a given hazy image. Dehazing algorithms are required in many situations, such as everyday photography, automatic surveillance systems, satellite remote sensing, outdoor object recognition, and visual navigation in low-visibility environments, etc. However, the image quality captured under severe weather conditions such as fog and haze is easily disturbed by the fog, which reduces the contrast of the captured image and seriously degrades the color. Such foggy images often lack visual vividness and clarity. Therefore, image dehazing techniques are urgently needed not only in everyday photography but also in many computer vision applications. [0003] At presen...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T5/00G06N3/04
CPCG06T5/003G06T5/009G06N3/045
Inventor 郭璠赵鑫唐琎吴志虎肖晓明高琰邹北骥
Owner CENT SOUTH UNIV
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