Efficient Assessment and Perception-Driven Optimization of Practical Image Rendering |
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With the advances in photography technologies, current image sensors are able to capture pictures with a high dynamic range up to eight orders of magnitude. However, existing monitors and projectors have a significantly limited dynamic range. When rendering high-dynamic-range (HDR) images on low-dynamic-range (LDR) display devices, tone mapping operators should be adopted for dynamic range compression. This project will describe a fair and efficient subjective assessment method by automatically sampling a minimum set of unbiased, diverse, and adaptive images that best differentiate among the competing methods. Moreover, we will take initial steps towards perception-driven optimization of HDR image rendering. We will also orient the proposed method within a perception-driven framework to assist machine in challenging low-light conditions. |
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