首页> 美国卫生研究院文献>Computational Intelligence and Neuroscience >Multiobjective Image Color Quantization Algorithm Based on Self-Adaptive Hybrid Differential Evolution
【2h】

Multiobjective Image Color Quantization Algorithm Based on Self-Adaptive Hybrid Differential Evolution

机译:基于自适应混合差分进化的多目标图像色彩量化算法

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

In recent years, some researchers considered image color quantization as a single-objective problem and applied heuristic algorithms to solve it. This paper establishes a multiobjective image color quantization model with intracluster distance and intercluster separation as its objectives. Inspired by a multipopulation idea, a multiobjective image color quantization algorithm based on self-adaptive hybrid differential evolution (MoDE-CIQ) is then proposed to solve this model. Two numerical experiments on four common test images are conducted to analyze the effectiveness and competitiveness of the multiobjective model and the proposed algorithm.
机译:近年来,一些研究人员将图像颜色量化视为单目标问题,并应用启发式算法对其进行了求解。建立了以簇内距离和簇间分离为目标的多目标图像色彩量化模型。受多种群思想的启发,提出了一种基于自适应混合差分演化(MoDE-CIQ)的多目标图像色彩量化算法来求解该模型。对四个通用测试图像进​​行了两个数值实验,以分析多目标模型和所提出算法的有效性和竞争力。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号