The iCAM06 has been used as an image appearance model for HDR image rendering. iCAM06 goes through the color space conversions of the several steps to present HDR images. The dynamic range of a HDR image needs to be mapped onto the range of output devices, which is called the tone mapping. However, tone compression process of iCAM06 causes white point shift and color distortion because of color-clipping and cross-stimulus. Therefore, we proposed a modified white-balanced method in low-chromatic region and a color adjustment method in IPT space to compensate the color distortion during in tone compression process. Through the experimental results, we confirmed the proposed compatible color adjustment method had better performance than iCAM06 and enhanced models.

Many High-Dynamic-Range (HDR) rendering techniques have been developed. Of these, the image color appearance model, iCAM, is a typical HDR image rendering algorithm. HDR rendering methods normally require a tone compression process and include many color space transformations from the RGB signal of an input image to the RGB signal of output devices for the realistic depiction of a captured image. The iCAM06, which is a refined iCAM, also contains a tone compression step and several color space conversions for HDR image reproduction. On the other hand, the tone compression and frequent color space changes in the iCAM06 cause color distortion, such as a hue shift and saturation reduction of the output image. To solve these problems, this paper proposes a separate color correction method that has no effect on the output luminance values by controlling only the saturation and hue of the color attributes. The color saturation of the output image was compensated for using the compensation gain and the hue shift was corrected using the rotation matrix. The separate color correction method reduces the existing color changes in iCAM06. The compensation gain and rotation matrix for the color correction were formulated based on the relationship between the input and output tristimulus values through the tone compression. The experimental results show that the revised iCAM06 with the proposed method has better performance than the default iCAM06.

Recently, a new image appearance model, named iCAM06, was developed for High-Dynamic-Range (HDR) image rendering. The dynamic range of a HDR image needs to be mapped onto the range of the output device where it will be displayed, this is called tone reproduction or tone mapping. iCAM06, a representative HDR rendering algorithm also uses tone compression for image reproduction on the dynamic range of output devices. However, iCAM06 causes a white point shift during its tone compression process. Therefore, we propose a compensation method for white point shifts using corrected channel gain. Experiment results show that the proposed method has better performance than iCAM06.

An image appearance model called iCAM06 was designed for high dynamic range (HDR) image rendering. The dynamic range of an HDR image needs to be mapped on output devices, which is called tone compression or tone mapping. The iCAM06, the representative HDR rendering algorithm, uses tone compression for image reproduction on the low dynamic range of output devices. However, color saturation reduction occurs during its tone compression process. We propose a saturation correction method using the inverse compensation in order to recover the saturation reduction in the iCAM06. Experimental results show that the proposed method has better performance than the iCAM06 from the viewpoint of saturation accuracy and rendering preference.

The Processing of high-dynamic-range (HDR) images is embodied by a lot of algorithms. This paper takes notice of one of these algorithms which is presented using the iCAM06. iCAM06 is capable of making color appearance predictions of HDR images based on CIECAM02 color predictions and incorporating spatial process models in the human visual system (HVS) for contrast enhancement. The effect of user controllable factors of iCAM06 was investigated and the best factor which corresponds with Breneman's corresponding color data sets was found. A suggested model improves color matching predictions for the corresponding color data set in Breneman's experiment.