Based on an extensive magnitude estimation experiment, a new color appearance model for unrelated self-luminous stimuli, CAM15u, has been designed. With the spectral radiance of the stimulus as unique input, the model predicts the brightness, hue, colorfulness, saturation and amount of white. The main features of the model are the use of the CIE 2006 cone fundamentals, the inclusion of an absolute brightness scale and a very simple calculation procedure. The CAM15u model performs much better than existing models and has been validated by a validation experiment. The model is applicable to unrelated self-luminous stimuli with an angular extent of 10° and a photopic, but non-glare-inducing, luminance level.

The perception of brightness of unrelated self-luminous colored stimuli of the same luminance has been investigated. The Helmholtz-Kohlrausch (H-K) effect, i.e., an increase in brightness perception due to an increase in saturation, is clearly observed. This brightness perception is compared with the calculated brightness according to six existing vision models, color appearance models, and models based on the concept of equivalent luminance. Although these models included the H-K effect and half of them were developed to work with unrelated colors, none of the models seemed to be able to fully predict the perceived brightness. A tentative solution to increase the prediction accuracy of the color appearance model CAM97u, developed by Hunt, is presented.

In a magnitude estimation experiment, twenty observers rated the brightness of several unrelated, self-luminous stimuli surrounded by a dark background. The performance of a number of existing vision models, color appearance models and models based on the concept of equivalent luminance in predicting brightness has been investigated. Due to a severe underestimation of the Helmholtz-Kohlrausch effect, none of the models performed acceptable. Increasing the weight of the colorfulness contribution to the brightness attribute in the CAM97u model results in a very good correlation between the model predictions and the visually perceived brightness. Finally the experimental results and the brightness prediction from the modified model CAM97u,m are verified through a matching experiment and a validation magnitude estimation experiment.

In a series of magnitude estimation experiments, the effect of the size of a circular stimulus varying from 1° to 30° field of view on the perception of brightness has been investigated for unrelated self-luminous stimuli. A clear, hue independent, size effect on brightness was found. Based on a simple modification of the recently developed Color Appearance Model CAM15u, the brightness of different sized unrelated self-luminous stimuli was adequately predicted. The modified brightness prediction performs much better than existing predictions and has been validated by a separate validation experiment.

Multi-exposure high dynamic range(HDR) imaging builds HDR radiance maps by stitching together different views of a same scene with varying exposures. Practically, this process involves converting raw sensor data into low dynamic range (LDR) images, estimate the camera response curves, and use them in order to recover the irradiance for every pixel. During the export, applying white balance settings and image stitching, which both have an influence on the color balance in the final image. In this paper, we use a calibrated quasi-monochromatic light source, an integrating sphere, and a spectrograph in order to evaluate and compare the average spectral response of the image sensor. We finally draw some conclusion about the color consistency of HDR imaging and the additional steps necessary to use multi-exposure HDR imaging as a tool to measure the physical quantities such as radiance and luminance.