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Figure 1: Image reproduced adaptively for low ambient light (dark room scenario -left) and high ambient light (sunlight scenario -right). The display adaptive tone mapping can account for screen reflections when generating images that optimize visible contrast. AbstractWe propose a tone mapping operator that can minimize visible contrast distortions for a range of output devices, ranging from e-paper to HDR displays. The operator weights contrast distortions according to their visibility predicted by the model of the human visual system. The distortions are minimized given a display model that enforces constraints on the solution. We show that the problem can be solved very efficiently by employing higher order image statistics and quadratic programming. Our tone mapping technique can adjust image or video content for optimum contrast visibility taking into account ambient illumination and display characteristics. We discuss the differences between our method and previous approaches to the tone mapping problem.

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As the performance of electronic display systems continues to increase, the limitations of current signal coding methods become more and more apparent. With bit depth limitations set by industry standard interfaces, a more efficient coding system is desired to allow image quality to increase without requiring expansion of legacy infrastructure bandwidth. A good approach to this problem is to let the human visual system determine the quantization curve used to encode video signals. In this way optimal efficiency is maintained across the luminance range of interest, and the visibility of quantization artifacts is kept to a uniformly small level.

New imaging and rendering systems commonly use physically accurate lighting information in the form of highdynamic range (HDR) images and video. HDR images contain actual colorimetric or physical values, which can span 14 orders of magnitude, instead of 8-bit renderings, found in standard images. The additional precision and quality retained in HDR visual data is necessary to display images on advanced HDR display devices, capable of showing contrast of 50,000:1, as compared to the contrast of 700:1 for LCD displays. With the development of high-dynamic range visual techniques comes a need for an automatic visual quality assessment of the resulting images.In this paper we propose several modifications to the Visual Difference Predicator (VDP). The modifications improve the prediction of perceivable differences in the full visible range of luminance and under the adaptation conditions corresponding to real scene observation. The proposed metric takes into account the aspects of high contrast vision, like scattering of the light in the optics (OTF), nonlinear response to light for the full range of luminance, and local adaptation. To calibrate our HDR VDP we perform experiments using an advanced HDR display, capable of displaying the range of luminance that is close to that found in real scenes.