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Optimizing Luminance and Chrominance Filtered Channels by Binary Genetic Algorithm (Bga) to Generate Color Halftone Image

机译:通过二进制遗传算法(BGA)优化亮度和色度滤波通道,以生成颜色半色调图像

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In the following approach, RGB images were converted into modified CIElab version i.e. linearized color space Yy,Cx,Cz. Here color channel Yy has been filtered through contrast sensitivity function of luminance channel. Cx and Cz color channel has been filtered through Chrominance contrast sensitivity function (CSF) model. The filtered data had been divided into 4*4 blocks. Binary pattern for each channel has been compared with original image datasets and error has been calculated. The error has been minimized by the binary genetic algorithm. The halftone pattern has been generated for each channel and it has been superimposed to generate the modified halftone image. The generated halftoned image has been compared to the original RGB image visually and mathematically. This work was done using R2007b simulator of MATLAB.
机译:在以下方法中,RGB图像被转换为​​修改的CIELAB版本i.e.线性化颜色空间YY,CX,CZ。这里通过亮度通道的对比度灵敏度函数过滤了颜色通道YY。 CX和CZ颜色通道通过色度对比度灵敏度(CSF)模型过滤。过滤的数据已分为4 * 4个块。将每个通道的二进制模式与原始图像数据集进行比较,并且已经计算了错误。通过二进制遗传算法最小化了错误。已经为每个通道生成了半色调模式,并且已经叠加以生成修改的半色调图像。已经在视觉上和数学上将生成的半色调图像与原始RGB图像进行了比较。这项工作是使用MATLAB的R2007B模拟器完成的。

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