Optimal Global Approximation to Spatially Varying Tone Mapping Operators
Our method is based on a modification of the simple but elegant constrained optimization technique called Pool-Adjacent- Violators-Algorithm (PAVA). In a second step, we show how any lost local detail can be brought back through copying, in an edge sensitive manner, detail from the original input (an approach already developed in the literature).
Our new global tone-curve approach has a specific advantage: we show it suffices to learn the tone-curve by processing a small thumbnail and then produce the final output by applying the tone-curve to the full resolution input. Not only does processing on thumbnails deliver excellent results we can, using this approach, significantly increase the speed of tone-mapping operators.
To evaluate our method we carried out a paired comparison psychophysical experiment. Preference scores resulting from the experiment show that in general the perceived quality of our proposed operator is similar (equally preferred) to a range of spatially-varying tone-mapping operators.
Document Type: Research Article
Publication date: January 1, 2012
Started in 2002 and merged with the Color and Imaging Conference (CIC) in 2014, CGIV covered a wide range of topics related to colour and visual information, including color science, computational color, color in computer graphics, color reproduction, volor vision/psychophysics, color image quality, color image processing, and multispectral color science. Drawing papers from researchers, scientists, and engineers worldwide, DGIV offered attendees a unique experience to share with colleagues in industry and academic, and on national and international standards committees. Held every year in Europe, DGIV papers were more academic in their focus and had high student participation rates.
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