A classic photographic task is the mapping of the potentially high dynamic range of real world luminances to the low dynamic range of the photographic print. This tone reproduction problem is also faced by computer graphics practitioners who map digital images to a low dynamic range print or screen. The work presented in this paper leverages the time-tested techniques of photographic practice to develop a new tone reproduction operator. In particular, we use and extend the techniques developed by Ansel Adams to deal with digital images. The resulting algorithm is simple and produces good results for a wide variety of images.

Color image quality depends on many factors, such as the initial capture system and its color image processing, compression, transmission, the output device, media and associated viewing conditions. In this paper, we are primarily concerned with color image quality in relation to compression and transmission. We review the typical visual artifacts that occur due to high compression ratios and/or transmission errors. We discuss color image quality metrics and present no-reference artifact metrics for blockiness, blurriness, and colorfulness. We show that these metrics are highly correlated with experimental data collected through subjective experiments. We use them for no-reference video quality assessment in di#erent compression and transmission scenarios and again obtain very good results. We conclude by discussing the important e#ects viewing conditions can have on image quality.

Gamut-mapping experiments were performed to test a set of general-purpose gamut-mapping functions. These gamutmapping algorithms utilized contrast-preserving scaling functions. These algorithms were tested against the GCUSP gamut-mapping algorithm proposed by Morovic and Luo, 1 which was shown to have very good "universal" gamutmapping characteristics. The results of these experiments showed that vast improvements were obtained when linear lightness and chroma rescaling functions are replaced with contrast-preserving lightness and chroma rescaling functions. For these experiments, the gamut mapping consisted of sigmoidal lightness remapping functions 2,3 followed by either "knee" functions 4,5 or "sigmoid-like" chromatic compression functions. Introduction The importance of color gamut mapping as a fundamental component of the color imaging chain has been brought to the forefront in recent years with the formation of the CIE Technical Committee 8-3. Specifically, research has be...

This paper describes the specifications and usage of standard RGB color spaces promoted today by standard bodies and/or the imaging industry. As in the past, most of the new standard RGB color spaces were developed for specific imaging workflow and applications. They are used as interchange spaces to communicate color and/or as working spaces in imaging applications. Standard color spaces can facilitate color communication: if an image is in `knownRGB,' the user, application, and/or device can unambiguously understand the color of the image, and further color manage from there if necessary. When applied correctly, a standard RGB space can minimize color space conversions in an imaging workflow, improve image reproducibility, and facilitate accountability.

We present a tone mapping algorithm that is derived from a model of retinal processing. Our approach has two major improvements over existing methods. First, tone mapping is applied directly on the mosaic image captured by the sensor, analogue to the human visual system that applies a non-linearity on the chromatic responses captured by the cone mosaic. This reduces the number of necessary operations by a factor three. Second, we introduce a variation of the center/surround class of local tone mapping algorithms, which are known to increase the local contrast of images but tend to create artifacts. Our method gives a good improvement in contrast while avoiding halos and maintaining good global appearance. Like traditional center/surround algorithms, our method uses a weighted average of surrounding pixel values. Instead of using it directly, the weighted average serves as a variable in the Naka-Rushton equation, which models the photoreceptors non-linearity. Our algorithm provides pleasing results on various images with different scene content and dynamic range.

Pixel saturation, in which the incident light at a pixel causes one of the color channels of the camera sensor to respond at its maximum value, can produce undesirable artifacts in digital color images. We present a Bayesian algorithm that estimates what the saturated channel’s value would have been in the absence of saturation. The algorithm uses the nonsaturated responses from the other color channels, together with a multivariate normal prior that captures the correlation in response across color channels. The prior may be estimated directly from the image data, since most image pixels are not saturated. Given the prior and the responses of the nonsaturated channels, the algorithm returns the optimal expected mean square estimate for the true response. Extensions of the algorithm to the case in which more than one channel is saturated are also discussed. Both simulations and examples with real images are presented to show that the algorithm is

We study the influence of the choice of color space for local tone mapping methods. Many local tone mapping methods do not perform well when applied independently to the three color channels of an RGB image. A common solution is to only treat the luminance channel. However, the question of which color space provides the most suitable luminance definition has not been addressed. The correlation between luminance and chrominance is known to have an influence on the rendered image but the relation between a measure of correlation and the appearance of the image has not yet been found. We consider four color transforms and introduce a measure to evaluate how well they decorrelate luminance and chrominance information. We apply two local tone mapping algorithms to the luminance channel given by the four transforms and visually compare the results. As each transform leads to another luminance definition, the resulting color images will be different as well. Our results confirm that less correlation between luminance and chrominance results in better performance of the local tone mapping algorithms. Namely, they provide a better increase in local contrast in the luminance channel and less hue shifts. However, we show that a perfect decorrelation is not always necessary.

characteristics Abstract. Tone mapping refers to the conversion of luminance values recorded by a digital camera or other acquisition device, to the luminance levels available from an output device, such as a monitor or a printer. Tone mapping can improve the appearance of rendered images. Although there are a variety of algorithms available, there is little information about the image tone characteristics that produce pleasing images. We devised an experiment where preferences for images with different tone characteristics were measured. The results indicate that there is a systematic relation between image tone characteristics and perceptual image quality for images containing faces. For these images, a mean face luminance level of 46–49 CIELAB L * units and a luminance standard deviation (taken over the whole image) of 18 CIELAB L * units produced the best renderings. This information is relevant for the design of tone-mapping algorithms, particularly as many images taken by digital camera users include faces. © 2005 SPIE and IS&T. [DOI: 10.1117/1.1900134] 1

This paper outlines several methods for determining 3x3 matrix transformations from camera spectral spaces to a standard color space based on the ITU-R BT.709 red, green, and blue (RGB) primaries

A simultaneous equisection experiment using a CRT in a dark surround was performed to investigate the relationship between a uniform background and the perception of lightness. The resulting curves for different backgrounds show both exponential properties, for black and white backgrounds, and sigmoidal characteristics, for intermediate grays. The sigmoidal properties are due to crispening and roughly intersect the diagonal or identity at the lightness of the background. The simultaneous contrast is greatest for the middle gray and decreases as the device white and black points are approached. An example equation is provided to fit the observations. This equation has as its input the L * of the stimuli and the background and has two fitting parameters. The issue of lightness scaling for backgrounds is also considered and finally extensions to this research are briefly mentioned.