Parameter Estimation of PuRet Algorithm for Managing Appearance of Material Objects on Display Devices

• Published in: Electronic Imaging no. 15; pp. 60404-1 - 60404-7
• Main Authors: Tanaka, Midori, Arai, Ryusuke, Horiuchi, Takahiko
• Format: Journal Article
• Language: English; Japanese
• Published: 7003 Kilworth Lane, Springfield, VA 22151 USA Society for Imaging Science and Technology 01.11.2019
• Subjects: Image Enhancement; Material Appearance; Material Perception
• ISSN: 2470-1173
• DOI: 10.2352/J.ImagingSci.Technol.2019.63.6.060404

In addition to colors and shapes, factors of material appearance such as glossiness, translucency, and roughness are important for reproducing the realistic feeling of an image. In general, these perceptual qualities are often degraded when reproduced as a digital color image. The authors have aimed to edit the material appearance of an image as measured by a general camera and reproduce it on a general display device. In their previous study, the authors found that the pupil diameter decreases slightly when observing the surface properties of an object and proposed an algorithm called "PuRet" for enhancing the material appearance based on the physiological models of the pupil and retina. However, to obtain an accurate reproduction, it was necessary to manually adjust two types of adaptation parameters in PuRet as related to the retinal response for each scene and the particular characteristics of the display device. This study realizes the management of the appearance of material objects on display devices by automatically deriving the optimum parameters in PuRet from captured RAW image data. The results indicate that the authors succeeded in estimating an adaptation parameter from the median value of the scene luminance as estimated from a RAW image. They also succeeded in estimating another adaptation parameter from the average value of the scene luminance and the luminance contrast value of the output display device. As a result of an experiment using an unknown display device that was not applied to derive the estimation model, it was confirmed that the proposed model works properly.