Skip to Main Content
This paper presents a novel tone mapping framework. First, we introduce a tone mapping fidelity principle which explicitly stipulates that tone-mapped image data should not only be visually enhanced but should also stay faithful to the original image. Second, this principle naturally translates tone mapping into a constrained optimization problem where a two-term cost function, one measures the difference between the tone mapped image and a visually enhanced version of the image, and the other measures the difference between the tone mapped image and the original image, is optimized. The relative weightings of the two terms in the cost function not only offers an insightful and simple mechanism to control the appearance of the tone mapped image but also enables the introduction of spatially varying or uniform weighting functions thus unifying local and global tone mapping in a single framework. We present results of tone mapping high dynamic range (HDR) images and low dynamic range JPEG images to demonstrate the effectiveness of the new tone mapping framework.