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Image defogging method based on variational method

A variational method and image technology, applied in the field of image processing, can solve the problems of slow processing speed, inability to dynamically adaptively adjust, and halo in the sky area, and achieve the effect of low memory consumption and simple operation.

Inactive Publication Date: 2013-04-10
XIAMEN UNIV
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Problems solved by technology

[0004] Chinese patent 201010139441.1 discloses an automatic image defogging method based on dark channels. This method uses dark channel priors to obtain transmission images, and multi-scale Retinex to obtain brightness component images. The processing speed is slow, and the lower threshold of the transfer function cannot be dynamically adjusted. Adaptive adjustment, the presence of halos in the processed sky area

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  • Image defogging method based on variational method
  • Image defogging method based on variational method
  • Image defogging method based on variational method

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[0042] In order to make the purpose, technical solutions and advantages of the present invention clearer, the embodiments of the present invention will be further described below in conjunction with the accompanying drawings:

[0043] see figure 1 , the realization method of dehazing mainly has three steps:

[0044] Step 1: Obtain the observed image under the minimum channel, and construct the objective function of the atmospheric penetration image under the variational framework.

[0045] The variational method is to construct a series of functions that can reflect the inherent properties of variables, and aim at the optimal output of the objective function formed by these functions, and finally obtain a mathematical solution to the estimated value of the variable. For the optical model of fog imaging, the objective function of the atmospheric penetration image is constructed under the variational framework, and the specific steps are as follows:

[0046] Step 1: Normalize ...

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Abstract

The invention discloses an image defogging method based on a variational method, relates to image processing, and aims to provide a image defogging method which can rapidly processes a foggy image to obtains a better clear result and meet the real-time processing requirements of an embedded device on the premise of ensuring the subjective visual effect. The method comprises the following steps: 1) constructing the objective function of an atmosphere-permeated image under a variational frame; 2) according to the constructed objective function, utilizing the open operation in morphology to calculate the image to obtain the atmosphere-permeated image; and 3) according to an atmospheric scattering physical model and the atmosphere-permeated image obtained through calculation, defogging and recovering the foggy image. The method is established on the basis of the variational method, the calculation is simple, the memory consumption is small, and the real-time processing requirements of the embedded device can be met.

Description

technical field [0001] The invention relates to image processing, in particular to an image defogging method based on a variational method. Background technique [0002] Fog is a common weather phenomenon in nature. In coastal and near-river areas, affected by evaporation of water vapor, this common natural weather occurs more frequently. Fog can play a very good embellishment effect on the natural landscape, but at the same time it also interferes with people's normal life to a large extent, such as affecting the effect of outdoor monitoring and increasing the incidence of traffic accidents. Fog has a great impact on the performance of intelligent devices based on images and videos. Under foggy weather conditions, the image quality of the scene captured by the camera is poor, which is manifested in: low contrast, blurred details and different degrees of color offset. [0003] The research on the dehazing algorithm of foggy images has great significance for improving the ...

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Application Information

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IPC IPC(8): G06T5/00
Inventor 丁兴号吴笑天傅雪阳郭伟金文博
Owner XIAMEN UNIV
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