BREN: Body Reflection Essence-Neuter Model for Separation of Reflection Components
This work addresses a specific problem in computer vision for image processing applications, representing an incremental advancement over existing methods.
The paper tackles the problem of separating dichromatic reflection components from a single image by introducing a novel reflection color model called BREN, which uses body essence and neuter to achieve insensitivity to noise and effectiveness across both RGB and CMY colors, with experimental results demonstrating its efficacy.
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.