Visual clutter concerns designers of user interfaces and information visualizations. This should not surprise visual perception researchers because excess and/or disorganized display items can cause crowding, masking, decreased recognition performance due to occlusion, greater difficulty at both segmenting a scene and performing visual search, and so on. Given a reliable measure of the visual clutter in a display, designers could optimize display clutter. Furthermore, a measure of visual clutter could help generalize models like Guided Search (J. M. Wolfe, 1994) by providing a substitute for "set size" more easily computable on more complex and natural imagery. In this article, we present and test several measures of visual clutter, which operate on arbitrary images as input. The first is a new version of the Feature Congestion measure of visual clutter presented in R. Rosenholtz, Y. Li, S. Mansfield, and Z. Jin (2005). This Feature Congestion measure of visual clutter is based on the analogy that the more cluttered a display or scene is, the more difficult it would be to add a new item that would reliably draw attention. A second measure of visual clutter, Subband Entropy, is based on the notion that clutter is related to the visual information in the display. Finally, we test a third measure, Edge Density, used by M. L. Mack and A. Oliva (2004) as a measure of subjective visual complexity. We explore the use of these measures as stand-ins for set size in visual search models and demonstrate that they correlate well with search performance in complex imagery. This includes the search-in-clutter displays of J. M. Wolfe, A. Oliva, T. S. Horowitz, S. Butcher, and A. Bompas (2002) and Bravo and Farid (2004), as well as new search experiments. An additional experiment suggests that color variability, accounted for by Feature Congestion but not the Edge Density measure or the Subband Entropy measure, does matter for visual clutter.

Human observers can distinguish the albedo of real-world surfaces even when the surfaces are viewed in isolation, contrary to the Gelb effect. We sought to measure this ability and to understand the cues that might underlie it. We took photographs of complex surfaces such as stucco and asked observers to judge their diffuse reflectance by comparing them to a physical Munsell scale. Their judgments, while imperfect, were highly correlated with the true reflectance. The judgments were also highly correlated with certain image statistics, such as moment and percentile statistics of the luminance and subband histograms. When we digitally manipulated these statistics in an image, human judgments were correspondingly altered. Moreover, linear combinations of such statistics allow a machine vision system (operating within the constrained world of single surfaces) to estimate albedo with an accuracy similar to that of human observers. Taken together, these results indicate that some simple image statistics have a strong influence on the judgment of surface reflectance.

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Figure 1: Undesirable artifacts in photography can be reduced by comparing image gradients at corresponding locations in a pair of flash and ambient images. (Left) Removing flash hot spot. Flash and ambient images of a museum scene, where the flash image reveals more of the scene but includes a strong highlight. We combine gradients in flash and ambient images to produce an enhanced flash image with the highlight removed. (Right) Removing self reflections. Flash and ambient images of a painting, where the ambient image includes annoying reflections of the photographer. The low-exposure flash image avoids reflections, but has a hot spot. We remove the reflections in the ambient image by removing the component of the ambient image gradients perpendicular to the flash image gradients. For visual verification, we show the computed reflection layer. AbstractFlash images are known to suffer from several problems: saturation of nearby objects, poor illumination of distant objects, reflections of objects strongly lit by the flash and strong highlights due to the reflection of flash itself by glossy surfaces. We propose to use a flash and no-flash (ambient) image pair to produce better flash images. We present a novel gradient projection scheme based on a gradient coherence model that allows removal of reflections and highlights from flash images. We also present a brightness-ratio based algorithm that allows us to compensate for the falloff in the flash image brightness due to depth. In several practical scenarios, the quality of flash/no-flash images may be limited in terms of dynamic range. In such cases, we advocate using several images taken under different flash intensities and exposures. We analyze the flash intensity-exposure space and propose a method for adaptively sampling this space so as to minimize the number of captured images for any given scene. We present several experimental results that demonstrate the ability of our algorithms to produce improved flash images.

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The U. S. government's failure to provide adequate oversight and prudent regulation of the financial markets, together with excessive risk taking by some financial institutions, pushed the world financial system to the brink of systemic failure in 2008. As a consequence of this near catastrophe, both regulators and investors have become keenly interested in developing tools for monitoring systemic risk. But this is easier said than done. Securitization, private transacting, complexity, and "flexible" accounting 6 prevent us from directly observing the many explicit linkages of financial institutions. As an alternative, we introduce a measure of implied systemic risk called the absorption ratio, which equals the fraction of the total variance of a set of asset returns explained or "absorbed" by a fixed number of eigenvectors. 7 The absorption ratio captures the extent to which markets are unified or tightly coupled. When markets are tightly 1 We thank Timothy Adler, Robin Greenwood, and participants of seminars at the European Quantitative Forum, the International Monetary Fund, PIMCO, QWAFAFEW, and State Street Associates for helpful comments.

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Solar steam generation by direct harvesting of light irradiation has emerged as one of most efficient technologies for utilization of solar energy and production of fresh water.