High dynamic range (HDR) images and video require tone-mapping for display on low dynamic range (LDR) screens. Many tone-mapping operators have been proposed to convert HDR content to LDR, but almost each has a different implementation structure and requires a different execution time. We propose a unified structure that can represent any global tone-mapping algorithm with an array of just 256 coefficients. These coefficients extracted offline for every HDR image or video frame can be used to convert them to LDR in real time using linear interpolation. The produced LDR images are identical to the images produced by the original implementation of the algorithm. This unified implementation can replicate any global tone-mapping function and requires very low and fixed execution time, which is independent of algorithm and type of content and depends only on image size. Experimental studies are presented to show the accuracy and time efficiency of the proposed implementation.
Citation: Ishtiaq Rasool Khan, Susanto Rahardja. Unified implementation of global high dynamic range image tone-mapping algorithms[J]. Mathematical Biosciences and Engineering, 2022, 19(5): 4643-4656. doi: 10.3934/mbe.2022215
High dynamic range (HDR) images and video require tone-mapping for display on low dynamic range (LDR) screens. Many tone-mapping operators have been proposed to convert HDR content to LDR, but almost each has a different implementation structure and requires a different execution time. We propose a unified structure that can represent any global tone-mapping algorithm with an array of just 256 coefficients. These coefficients extracted offline for every HDR image or video frame can be used to convert them to LDR in real time using linear interpolation. The produced LDR images are identical to the images produced by the original implementation of the algorithm. This unified implementation can replicate any global tone-mapping function and requires very low and fixed execution time, which is independent of algorithm and type of content and depends only on image size. Experimental studies are presented to show the accuracy and time efficiency of the proposed implementation.
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