Vision Models for High Dynamic Range and Wide Colour Gamut Imaging: Techniques and Applications (Computer Vision and Pattern Recognition)

To enhance the overall viewing experience (for cinema, TV, games, AR/VR) the media industry is continuously striving to improve image quality. Currently the emphasis is on High Dynamic Range (HDR) and Wide Colour Gamut (WCG) technologies, which yield images with greater contrast and more vivid colours. The uptake of these technologies, however, has been hampered by the significant challenge of understanding the science behind visual perception. Vision Models for High Dynamic Range and Wide Colour Gamut Imaging provides university researchers and graduate students in computer science, computer engineering, vision science, as well as industry R&D engineers, an insight into the science and methods for HDR and WCG. It presents the underlying principles and latest practical methods in a detailed and accessible way, highlighting how the use of vision models is a key element of all state-of-the-art methods for these emerging technologies. Presents the underlying vision science principles and models that are essential to the emerging technologies of HDR and WCG Explores state-of-the-art techniques for tone and gamut mapping Discusses open challenges and future directions of HDR and WCG research Introduction The biological basis of vision: the retina The biological basis ov vision: LGN, visual cortex and L+NL models Adaptation and efficient coding Brightness perception and encoding curves Colour representation and colour gamuts Histogram equalisation and vision models Vision models for gamut mapping in cinema Vision models for tone mapping in cinema Extensions and applications Open problems: an argument for new vision models rather than new algorithms