Moment based normalization of color images
Moment based normalization of color images
复制标题
彩色图像基于矩的归一化
DOI：
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发表时间：
1999
期刊：
影响因子：
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通讯作者：
P. Meer
中科院分区：
文献类型：
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作者：
R. Lenz;L. Tran;P. Meer
在许多多媒体应用中，期望将照明源和成像设备的影响与所描绘场景的属性分开。人类视觉系统在许多情况下解决这个任务的能力被称为颜色恒定性。这些方法的技术应用包括图像数据库中的自动颜色校正和照明独立搜索。许多传统的计算颜色恒定性方法假设照明变化的效果可以通过与对角矩阵的矩阵乘法来描述。在本文中，我们介绍了一种颜色归一化算法，该算法计算唯一的颜色变换矩阵，该矩阵归一化从图像的颜色分布计算的一组给定的矩。由于考虑了一般的矩阵变换，因此该归一化过程是通道无关颜色恒常性方法的推广。我们比较了这种新的归一化方法与传统的颜色恒常性方法的性能。实验表明，对角变换矩阵提供了一个更好的照明补偿。这表明，颜色矩也包含了重要的信息的颜色分布的对象在图像中，这是独立的照明特性。在另一组实验中，我们使用唯一的变换矩阵作为描述图像中全局颜色分布的矩集的描述符。结合从两个这样的图像计算的矩阵描述它们之间的颜色差异。然后，我们使用它作为一个工具，在图像数据库中的颜色相关的搜索。这种基于矩阵的颜色搜索在计算上比基于直方图的颜色搜索工具要求更低。
In many multi-media applications it is desirable to separate the influence of the illumination sources and imaging equipment from the properties of the depicted scene. The ability of the human visual system to solve this task in many situations is known as color constancy. Technical applications of these methods include automatic color correction and illumination independent search in image databases. Many conventional computational color constancy methods assume that the effect of an illumination change can be described by a matrix multiplication with a diagonal matrix. In this paper we introduce a color normalization algorithm which computes the unique color transformation matrix which normalizes a given set of moments computed from the color distribution of an image. This normalization procedure is a generalization of the channel independent color constancy methods since general matrix transformations are considered. We compare the performance of this new normalization method with conventional color constancy methods. The experiments show that diagonal transformation matrices provide a better illumination compensation. This shows that the color moments also contain significant information about the color distributions of the objects in the image which is independent of the illumination characteristics. In another set of experiments we use the unique transformation matrix as a descriptor of the set of moments which describe the global color distribution in the image. Combining the matrices computed from two such images describes the color differences between them. We then use this as a tool for color dependent search in image databases. This matrix based color search is computationally less demanding than histogram based color search tools.