计算机彩色模型在图像显示与分割中的应用

COLOR MODELS USED IN IMAGE REPRESENTATION AND SEGMENTATION

本文提出了基于彩色馍型的灰度图像彩色显示与分割的方法，该方法将RGB，HSV和GLHS这几个彩色模型用于图像彩色合成显示并首次用于庆度图像分割中．彩色合成利用图像增强方法并考虑到人眼对彩色的分辨率以及视觉特性，不仅增强了图像的内容，而且给予图像合理的彩色显示，使图像易于分析并且具有好的视觉效果．利用RGB，HSV和GLHS模型之间的转换，我们也将合成的彩色图像进行分解，用于灰度图像的目标分割中．本文提出的方法快速简便，适用于很多图像处理场合，如红外图像、遥感图像和医学图像的增强、显示与分割．

This paper proposes several efficient approaches for monochrome image representation and segmentation based on the color models of RGB, HSV and GLHS. The approaches, considering both gray level image intensity enhancement and the human visual characteristics of color sensitivity, not only transform the image into a more recognizable one, but also give the image its color representation. From the composite color representation and color decomposition using the conversion between the color models of RGB and HSV or GLHS, the objects can be effectively segmented in gray level images. The methods can be used in a lot of gray level image cases such as the infrared image, X-ray image and mammography. Some experimental results also be shown in this paper.