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Image enhancement method based on local search differential evolution

A technology of local search and differential evolution, applied in image enhancement, image data processing, graphics and image conversion, etc., can solve the problem of low enhancement efficiency, achieve the effect of improving the effect, avoiding falling into local optimum, and enhancing the quality

Active Publication Date: 2017-04-26
JIANGXI UNIV OF SCI & TECH
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Problems solved by technology

[0004] The present invention aims at the disadvantages that the traditional differential evolution algorithm is prone to fall into local optimum and the enhancement efficiency is not high when it is applied to image enhancement, and proposes an image enhancement method based on local search differential evolution

Method used

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  • Image enhancement method based on local search differential evolution
  • Image enhancement method based on local search differential evolution

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Embodiment

[0048] Step 1, enter such as figure 1 An image shown in IM;

[0049] Step 2, the user initializes the parameters, and the initialization parameters include the population size Popsize=20, the maximum number of evaluations MAX_FEs=80, the hybridization rate Cr=0.9 and the scaling factor F=0.6;

[0050] Step 3, let the current evolution algebra t=0, the current evaluation times FEs=0, and the number of optimized design parameters D=2;

[0051] Step 4, randomly initialize the population Where: individual subscript i=1,2,...,Popsize; for population P t The i-th individual in and stores two design parameters to be optimized;

[0052] Step 5, calculate the population P t each individual in fitness value Among them, individual subscript i=1,2,...,Popsize, individual fitness value The calculation method is: the individual Decode it into the parameters α, β of the incomplete Beta function, and use the incomplete Beta function with α, β as the parameter to perform nonline...

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Abstract

The invention discloses an image enhancement method based on local search differential evolution. A local search differential evolution algorithm is used to optimize the parameters of an incomplete Beta function. Then, an image is nonlinearly transformed based on the parameter-optimized incomplete Beta function, and thus, the quality of the image is enhanced. In the local search differential evolution algorithm, the basic individual of a differential mutation operator is generated based on the information of an optimal individual and a random individual to balance the population diversity and the convergence speed. In the process of search, a local search strategy is implemented to improve the effect of image enhancement. The method can avoid falling into local optimum to a certain extent and improve the effect of image enhancement.

Description

technical field [0001] The invention relates to the field of image enhancement, in particular to an image enhancement method based on local search differential evolution. Background technique [0002] Image enhancement is a common technique in digital image processing systems. In the process of digital image processing, due to the limitations of lighting and sensor hardware characteristics, the images obtained by people often have the problem of poor visual effect. To solve this problem, people often use nonlinear transformation methods to process images, so as to improve the quality of such images with poor visual effects. Image enhancement technology based on the principle of image nonlinear transformation has the advantages of easy implementation and high operating efficiency, so it is widely used in various digital image processing systems. The core problem of image enhancement technology based on nonlinear image transformation is how to effectively optimize the parame...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06T3/00
CPCG06T3/00G06T5/92
Inventor 郭肇禄王洋章银娥尹宝勇鄢化彪余法红李康顺
Owner JIANGXI UNIV OF SCI & TECH
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