Gamut Compression and Extension Algorithms Based on Observer Experimental Data
Gamut Compression and Extension Algorithms Based on Observer Experimental Data
复制标题
基于观察者实验数据的色域压缩与扩展算法
DOI：
10.4218/etrij.03.0102.3315
复制
发表时间：
2003
期刊：
影响因子：
1.4
通讯作者：
M. Cho
中科院分区：
文献类型：
--
作者：
Byoung;J. Morovič;M. Luo;M. Cho
色域压缩算法传统上被功能性地定义，然后用演绎方法进行测试，例如，心理物理实验我们的研究提供了一种替代方法，一种归纳方法，观察者判断图像颜色，以更准确地代表原始图像。我们开发了一种计算机控制的交互式工具，可以修改显示器上显示的图形图像的颜色外观。在实验中，观察者使用该工具根据它们所属的颜色空间区域来改变颜色像素。我们创建了三个不同的色域压缩算法的基础上观察者的实验数据。观察员小组评估了新开发的算法、现有色域压缩算法以及基于本研究中实验的平均观察员结果的图像的性能。
Gamut compression algorithms have traditionally been defined functionally and then tested with deductive methods, e.g., psychophysical experiments. Our study offers an alternative, an inductive method, in which observers judge image colors to represent the original images more accurately. We developed a computer‐controlled interactive tool that modifies the color appearance of pictorial images displayed on a monitor. In experiments, observers used the tool to alter color pixels according to the region of color space to which they belonged. We created three different gamut compression algorithms based on the observer experimental data. Observer groups evaluated the performance of the newly‐developed algorithms, existing gamut compression algorithms, and an image based on the average observers’ results from experiments in this study.