IEEE Trans Image Process. 2015 Mar;24(3):1115-26. doi: 10.1109/TIP.2015.2393056.
Perception of color varies markedly between individuals because of differential expression of photopigments in retinal cones. However, it has been difficult to quantify the individual cognitive variation in colored scene and to predict its complex impacts on the behaviors. We developed a method for quantifying and visualizing information loss and gain resulting from individual differences in spectral sensitivity based on visual salience. We first modeled the visual salience for color-deficient observers, and found that the predicted losses and gains in local image salience derived from normal and color-blind models were correlated with the subjective judgment of image saliency in psychophysical experiments, i.e., saliency loss predicted reduced image preference in color-deficient observers. Moreover,saliency-guided image manipulations sufficiently compensated for individual differences in saliency. This visual saliency approach allows for quantification of information extracted from complex visual scenes and can be used as an image compensation to enhance visual accessibility by color-deficient individuals.
由于视网膜锥体中视色素的差异表达，个体对颜色的感知差异很大。然而，量化个体对彩色场景的认知差异并预测其对行为的复杂影响一直很困难。我们开发了一种基于视觉显著性的方法来量化和可视化由于光谱灵敏度个体差异而导致的信息损失和增益。我们首先对色觉缺陷观察者的视觉显著性进行建模，发现从正常和色盲模型中得出的局部图像显著性的预测损失和增益与心理物理实验中图像显著性的主观判断相关，即显著性损失预测了色觉缺陷观察者对图像偏好的降低。此外，显著性引导的图像操作充分补偿了显著性的个体差异。这种视觉显著性方法可以量化从复杂视觉场景中提取的信息，并可用于图像补偿，以增强色觉缺陷个体的视觉可及性。
