Adaptive method for image dynamic range adjustment and detail enhancement.

Abstract

Tone mapping operators (TMOs) aim to adjust high dynamic range (HDR) images to low dynamic range (LDR) ones so that they can be displayed on conventional devices with visual information retained. Nonetheless, existing TMOs can successfully tone-map only limited types of HDR images, and the parameters need to be manually adjusted to yield the best subjective-quality tone-mapped outputs. To cope with the aforementioned issues, an adaptive parameter-free and scene-adaptive TMO for dynamic range adjusting and detail enhancing is proposed to yield a high-resolution and high-subjective-quality tone-mapped output. This method is based on detail/base layer decomposition to decompose the input HDR image into coarse detail, fine detail, and base images. After that, we adopt different strategies to process each layer to adjust the overall brightness and contrast and to retain as much scene information. Finally, a new method, to the best of our knowledge, is proposed for visualization to generate a sequence of artificial images to adjust the brightness. Experiments with numerous HDR images and state-of-the-art TMOs are conducted; the results demonstrate that the proposed method consistently produces better quality tone-mapped images than the state-of-the-art methods.