Contrast enhancement of medical images using a new version of the World Cup Optimization algorithm
Contrast enhancement of medical images using a new version of the World Cup Optimization algorithm
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DOI：
10.21037/qims.2019.08.19
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发表时间：
2019-09-01
影响因子：
2.8
通讯作者：
Jimenez, Giorgos
中科院分区：
文献类型：
--
作者：
Zhou, Yuanping;Shi, Changqin;Jimenez, Giorgos
背景：本文提出了一种优化增强医学图像对比度的新方法。主要思想是基于世界杯优化（WCO）算法的新设计，改进Gamma校正方法来增强和突出图像信息和细节。 Gamma 校正是一种适合对比度增强的方法，其效率直接取决于 Gamma 系数的正确选择。方法：在本研究中，采用一种新提出的算法，通过考虑熵、边缘内容和多目标优化来最佳选择 Gamma 值。结果：将模拟结果与 5 种最先进的方法进行比较，以展示方法的效率。为此，采用了对比度、均匀性、加权平均峰值信噪比 (WPSNR)、增强测量 (EME) 和对比度噪声比 (CNR)。 结论：最终结果表明，所提出的多目标优化算法提高了图像对比度的质量，并且比其他类似方法可以提供更多细节和信息。
Background: In this paper, a new method for optimal enhancement of the contrast of a medical image is proposed. The main idea is to improve the Gamma correction method to enhance and highlight the image information and the details based on a new design of the World Cup Optimization (WCO) algorithm. Gamma correction is a suitable method for contrast enhancement with an efficiency that directly depends on the correct selection of the Gamma coefficient.Methods: In this study, a newly presented algorithm was employed for optimal selection of the Gamma value by considering the entropy, edge content, and multi-objective optimization.Results: The simulation results were compared with 5 state of the art methods for presenting method efficiency. To do this, contrast, homogeneity, weighted average peak signal-to-noise ratio (WPSNR), measure of enhancement (EME), and contrast-to-noise ratio (CNR) were employed.Conclusions: Final results denote that the presented multi-objective optimization algorithm improves the quality of the image contrast and can provide more details and information than the other comparable methods.