基于灰度级分组的彩色图像均衡
首发时间:2011-08-22
摘要:目前图像处理领域已有几种经典的彩色图像直方图均衡法:基于颜色通道的独立均衡法、基于三维联合概率的均衡法、基于HSI颜色空间的I分量均衡法和基于HSI颜色空间的SI分量联合均衡法,这几种经典的方法对很多低对比度的图片处理效果不尽理想。基于灰度级分组(Gray-Level Grouping)的图像增强方法可以有效解决这种问题。本文将灰度级分组方法应用在彩色图像上,对彩色图像的RGB三分量分别采用灰度级分组法处理,还有对彩色图像的I分量采用灰度级分组法处理。经过结果对比,后者的效果比前者好。基于灰度级分组的彩色图像均衡与经典均衡法也作了比较,结果显示,对于一般的彩色图像来说,基于灰度级分组的彩色图像均衡与经典均衡法效果相差不大,而对于低对比度的彩色图像来说,前者效果明显很多。
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Color image histogram equalization based on Gray-Level Grouping
Abstract:Currently there are several classical image processing methods on color image histogram equalization: Dependent-equalization in RGB, 3D-equalization in RGB, I-equalization in HSI and SI-equalization in HSI, but these methods can not get perfect effects for some low-contrast images. Histogram equalization based on Gray-Level Grouping can solve the problem in this case. This paper has the Gray-Level Grouping used in color images, on the RGB components and the I in HSI. The latter works better. Color image histogram equalization based on Gray-Level Grouping , works as good as the classical color image histogram equalization on general images, however, on low-contrast images, it works much better than the classical color image histogram equalization.
Keywords: Signal and Information Processing Color image histogram equalization Gray-Level Grouping
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