BREN: Body Reflection Essence-Neuter Model for Separation of Reflection Components

TL;DR

This paper introduces BREN, a new reflection separation model using body essence and neuter, which effectively isolates reflection components from a single image, especially around CMY and RGB colors, without segmentation.

Contribution

The paper presents a novel reflection color model and an effective single-image separation method that is robust to noise and color variations, avoiding the need for region segmentation.

Findings

Effective separation of reflection components demonstrated.

Robustness to noise and color variations shown.

No region segmentation required for the method.

Abstract

We propose a novel reflection color model consisting of body essence and (mixed) neuter, and present an effective method for separating dichromatic reflection components using a single image. Body essence is an entity invariant to interface reflection, and has two degrees of freedom unlike hue and maximum chromaticity. As a result, the proposed method is insensitive to noise and proper for colors around CMY (cyan, magenta, and yellow) as well as RGB (red, green, and blue), contrary to the maximum chromaticity-based methods. Interface reflection is separated by using a Gaussian function, which removes a critical thresholding problem. Furthermore, the method does not require any region segmentation. Experimental results show the efficacy of the proposed model and method.