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首页> 外文会议>2016 Al-Sadiq International Conference on Multidisciplinary in IT and Communication Techniques Science and Applications >Color to grayscale image conversion based dimensionality reduction with Stationary Wavelet transform
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Color to grayscale image conversion based dimensionality reduction with Stationary Wavelet transform

机译：固定小波变换的彩色到灰度图像转换降维

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摘要

This paper exhibits a brisk and straightforward strategy for changing over coloring pictures to perceptually exact grayscale variants. Strategies performing the transform of color image to grayscale plans to hold however much data about the source color picture as could be expected subsequent to critical picture highlights regularly vanish when color images are convert over to grayscale representation because of dimensionality reduction or varying requirements between the source and target color spaces. In this research we exhibited another complexity improving contrast to grayscale transformation calculation which comprise from procedure steps. Firstly, transform over RGB inputs to a perceptually uniform CIE L*a*b* color space and utilize Helmholtz-Kohlrausch Predictors to corrects L* based on the color chromatic component C* and hue angle H to get enhanced L**. Secondly, Dimensionality Reduction connected to Chrominance channels utilizing key segment investigation. Thirdly, upgrade the resulted grayscale image to the physical luminance channel based on mathematical with α=0.01 to enhance the contrast of resulted grayscale image. At long last, two dimensional Stationary Wavelet Transform (SWT) is connected in one level for melded the came about picture from past stride with Luminosity component L** to get the last grayscale picture. The grayscale image created relied on upon the calculation in the experiment confirm that the calculation has protected the notable components of the shading picture, for example, contrasts, sharpness, shadow, and image structure as contrasted and as compared with recently algorithms.
机译：本文展示了一种快速而简单的策略，可以将彩色图片转换为可感知的精确灰度级变体。当彩色图像转换为灰度表示时，由于尺寸降低或源之间的要求不同，执行彩色图像到灰度计划的策略可以保存有关源彩色图片的大量数据，但是在关键图片高亮显示之后，这些数据经常会消失和目标色彩空间。在这项研究中，我们展示了另一种复杂性，它提高了与灰度转换计算的对比，后者包括过程步骤。首先，将RGB输入转换为感知上均匀的CIE L * a * b *颜色空间，并利用Helmholtz-Kohlrausch Predictors根据色度分量C *和色相角H校正L *，以获得增强的L **。其次，利用关键片段调查将降维连接到色度通道。第三，根据数学公式将生成的灰度图像升级到物理亮度通道，α= 0.01，以增强生成的灰度图像的对比度。最后，将二维平稳小波变换（SWT）一层连接在一起，以将过去的步幅图像与亮度分量L **融合在一起，以获得最后的灰度图像。根据实验中的计算创建的灰度图像证实，该计算已保护了阴影图片的显着组成部分，例如对比，与最近的算法相比，对比度，清晰度，阴影和图像结构。

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