Image-based Perceptual Editing: Leather “Authenticity” as a Case Study

Abstract

Traditionally, the appearance of an object in an image is edited to elicit a preferred perception. However, the editing method might be arbitrary and might not consider the human perception mechanism. In this study, the authors explored image-based leather “authenticity” editing using an estimation model that considers a perception mechanism derived in their previous work. They created leather rendered images by emphasizing or suppressing image properties corresponding to the “authenticity.” Subsequently, they performed two subjective experiments, one using fully edited images and another using partially edited images whose specular reflection intensity was constant. Participants observed the leather rendered images and evaluated the differences in the perception of “authenticity.” The authors found that the “authenticity” perception could be changed by manipulating the intensity of specular reflection and the texture (grain and surface irregularity) in the images. The results of this study could be used to tune the properties of images to make them more appealing.