Lossy compression algorithms used in digital video systems produce artifacts whose visibility strongly depends on the actual image content. Simple error measures such as RMSE or PSNR, albeit popular, ignore this important fact and are only a mediocre predictor of perceived quality. Many applications require more reliable assessment methods. This paper discusses issues in vision modeling for perceptual video quality assessment (PVQA). Its purpose is not to describe a particular model or system, but rather to summarize and to provide pointers to up-to-date knowledge of important characteristics of the human visual system, to explain how these characteristics may be incorporated in vision models for PVQA, to give a brief overview of the state-of-the-art and current efforts in this field, and to outline directions for future research.

Human vision takes time to adapt to large changes in scene intensity, and these transient adjustments have a profound effect on visual appearance. This paper offers a new operator to include these appearance changes in animations or interactive real-time simulations, and to match a user's visual responses to those the user would experience in a real-world scene. Large, abrupt changes in scene intensities can cause dramatic compression of visual responses, followed by a gradual recovery of normal vision. Asymmetric mechanisms govern these timedependent adjustments, and offer adaptation to increased light that is much more rapid than adjustment to darkness. We derive a new tone reproduction operator that simulates these mechanisms. The operator accepts a stream of scene intensity frames and creates a stream of color display images. All operator components are derived from published quantitative measurements from physiology, psychophysics, color science, and photography. Kept intentiona...

The ultimate aim of realistic graphics is the creation of images that provoke the same responses that a viewer would have to a real scene. This STAR addresses two related key problem areas in this effort which are located at opposite ends of the rendering pipeline, namely the data structures used to describe light during the actual rendering process, and the issue of displaying such radiant intensities in a meaningful way.

We introduce an active imaging method to measure scene illumination. The system implementation is divided into four steps. First, the system acquires two images: one is an ordinary image of the scene under ambient light and the other is a corresponding image in which light from the camera flash is added to the scene. Second, the image pair is analyzed to obtain an image that represents the scene as if it had been illuminated by the flash alone. Third, the flashonly image is used to estimate object reflectance functions. Fourth, using the estimated reflectance functions, the ambient illumination spectral power distribution is estimated. We present results that evaluate the method’s stability with respect to changes in the mean reflectance function of the scene. Finally, we discuss limitations of the current implementation and alternative implementations.

The ultimate aim of realistic graphics is the creation of images that provoke the same responses that a viewer would have to a real scene. While research into ways of rendering images provides us with better and faster methods, we do not necessarily see their full effect due to limitations of the display hardware. The low dynamic range of a standard computer monitor requires some form of mapping to produce images that are perceptually accurate. Tone reproduction operators attempt to replicate the effect of real-world luminance intensities. This paper reviews the work to date on tone reproduction techniques. It includes an investigation into the need for accurate tone reproduction and a discussion of techniques to date. The future of tone reproduction is considered, together with the implications of advances in display hardware.

The color we perceive at each point in an image depends on information spread across the three spatial arrays of cone photoreceptors. I describe experiments aimed at clarifying how information is integrated across the spatial arrays to yield a color experience. We have found that changes of color appearance due to changes of the ambient illumination and the pattern's spatial frequency can be described using a simple set of optical and neural transformations. Each transformation can be thought ofhaving two parts. First, the transformation converts the color representation into a new coordinate frame that is independent of the image contents. Second, the transformation scales the neural responses in the new coordinate frame by a gain factor that depends on the image contents.

Abstract not found

The traditional techniques of image capture, scanning, proofing, and separating do not take advantage of colorimetry and spectrophotometry. For critical color-matching applications such as catalog sales, art-book reproductions, and computer-aided design, typical images, although pleasing, are unacceptable with respect to color accuracy. The limitations that lead to these errors have a well-defined theoretical basis and are a result of current hardware and software. This has led us to a reexamination of the traditional graphic reproduction paradigm. A research and development program has begun that will alleviate the theoretical limitations associated with traditional techniques. There are four main phases: 1) Multi-spectral image capture, 2) Spectral-based separation and printing algorithm development, 3) Implementation on press, and 4) Systems integration with data and image archives. This paper describes this new paradigm, summarizes recent research results, and considers implementation opportunities.

Brainard, D. H., Pelli, D. G., & Robson, T. (2002). Display characterization. In J. Hornak (Ed.), Encyclopedia of Imaging Science and Technology (pp. 172-188): Wiley. http://www.psych.nyu.edu/pelli/pubs/brainard2002display.pdf

The use of mathematical morphology in low and mid-level image processing and computer vision applications has allowed the development of a class of techniques for analyzing shape information in monochrome images. In this paper these techniques are extended to color images. We investigate two approaches for "color morphology": a vector approach, in which color vectors are ranked using a multivariate ranking concept known as reduced ordering, and a component-wise approach, in which grayscale morphological operations are applied to each of the three color component images independently. New vector morphological filtering operations are defined, and a set-theoretic analysis of these vector operations is presented. We also present experimental results comparing the performance of the vector approach and the component-wise approach for two applications: multiscale color image analysis and noise suppression in color images. EDICS: IP 1.7 This work was partially supported by the National Scien...