Improved image display by identifying the RGB family color space

To display an image, the color space in which the image is encoded is assumed to be known. Unfortunately, this assumption is rarely realistic. In this paper, we propose to identify the color space of a given color image using pixel embedding and the Gaussian process. Five color spaces are supported, namely Adobe RGB, Apple RGB, ColorMatch RGB, ProPhoto RGB and sRGB. Using the DRESDEN (Gloe and Böhme, 2010) and RAISE (Dang-Nguyen et al., 2015) image collections, we achieve an identification rate of 68%, highlighting the need for further work on this issue. • Propose a novel approach to enhance the display quality of color images. • Tackle the challenge of accurately identifying RGB color spaces for image rendering. • Design a model using pixel embeddings and Gaussian processes to construct feature vectors for images. • Implement a lightweight classification model for efficient differentiation of RGB color spaces.