Quaternion Factorized Simulated Exposure Fusion.

Image Fusion maximizes the visual information at each pixel location by merging content from multiple images in order to produce an enhanced image. Exposure Fusion, specifically, fuses a bracketed exposure stack of poorly lit images to generate a properly illuminated image. Given a single input image, exposure fusion can still be employed on a ‘simulated’ exposure stack, leading to direct single image contrast and low-light enhancement. In this work, we present a novel ‘Quaternion Factorized Simulated Exposure Fusion’ (QFSEF) method by factorizing an input image into multiple illumination consistent layers. To this end, we use an iterative sparse matrix factorization scheme by representing the image as a two-dimensional pure quaternion matrix. Theoretically, our representation is based on the dichromatic reflection model and accounts for the two scene illumination characteristics by factorizing each progressively generated image into separate specular and diffuse components. We empirically prove the advantages of our factorization scheme over other exposure simulation methods by using it for the low-light image enhancement task. Furthermore, we provide three exposure fusion strategies which can be used with our simulated stack and provide a comprehensive performance analysis. Finally, in order to validate our claims, we show extensive qualitative and quantitative comparisons against relevant state-of-the-art solutions on multiple standard datasets along with relevant ablation analysis to support our proposition. Our code and data are publicly available for easy reproducibility and reference. 1