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.

We present a method for creating black-and-white illustrations from photographs of human faces. In addition an interactive technique is demonstrated for deforming these black-and-white facial illustrations to create caricatures which highlight and exaggerate representative facial features. We evaluate the effectiveness of the resulting images through psychophysical studies to assess accuracy and speed in both recognition and learning tasks. These studies show that the facial illustrations and caricatures generated using our techniques are as effective as photographs in recognition tasks. For the learning task we find that illustrations are learned two times faster than photographs and caricatures are learned one and a half times faster than photographs. Because our techniques produce images that are effective at communicating complex information, they are useful in a number of potential applications, ranging from entertainment and education to low bandwidth telecommunications and psychology research. Categories and Subject Descriptors: I.3.3 [Computer Graphics]: Picture/image Generation—bitmap and framebuffer operations;

A neural network model of boundary segmentation and surface representation is developed to process images containing range data gathered by a synthetic aperture radar (SAR) sensor. The boundary and surface processing are accomplished by an improved Boundary Contour System (BCS) and Feature Contour System (FCS), respectively, that have been derived from analyses of perceptual and neurobiological data. BCS/FCS processing makes structures such as motor vehicles, roads, and buildings more salient and interpretable to human observers than they are in the original imagery. Early processing by ON cells and OFF cells embedded in shunting centersurround network models preprocessing by lateral geniculate nucleus (LGN). Such preprocessing compensates for illumination gradients, normalizes input dynamic range, and extracts local ratio contrasts. ON cell and OFF cell outputs are combined in the BCS to define oriented filters that model cortical simple cells. Pooling ON and OFF outputs at simple cel...

A key goal of behavioral and cognitive neuroscience is to link brain mechanisms to behavioral functions. The present article describes recent progress towards explaining how the visual cortex sees. Visual cortex, like many parts of perceptual and cognitive neocortex, is organized into six main layers of cells, as well as characteristic sub-lamina. Here it is proposed how these layered circuits help to realize processes of development, learning, perceptual grouping, attention, and 3D vision through a combination of bottom-up, horizontal, and top-down interactions. A key theme is that the mechanisms which enable development and learning to occur in a stable way imply properties of adult behavior. These results thus begin to unify three fields: infant cortical development, adult cortical neurophysiology and anatomy, and adult visual perception. The identified cortical mechanisms promise to generalize to explain how other perceptual and cognitive processes work.

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¶ The authors wish to thank C. Bourassa for providing the data from his ganzfeld experiments. *Acknowledgments: The author wishes to thank Diana Meyers for her valuable assistance in the prepara-tion of this manuscript. i-1 How does the visual cortex combine information from both eyes to generate perceptual representa-tions of object surfaces? Important clues about this process may be derived from data about the perceived brightnesses of surface regions under binocular viewing conditions, including data about binocular bright-ness summation in response to ganzfelds, the U-shaped data of Fechner’s Paradox that violates binocular brightness summation, and the effects of different combinations of monocular and binocular contours and surface luminance differences on threshold sensitivity to monocular flashes of light. How to reconcile these apparently contradictory data properties has been a severe challenge to previous models, and none has explained them all. The present article quantitatively simulates them all by further developing the FACADE vision model. Key model processes discount the illuminant and compute image contrasts in each monocular channel using shunting on-center off-surround networks; binocularly fuse these discounted

A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids [Todd, J., & Akerstrom, R. (1987). Perception of three-dimensional form from patterns of optical texture. Journal of Experimental Psychology: Human Perception and Performance, 13(2), 242–255]. In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.

ist m oglicherweise der Grund f ur die physiologisch gemessene dominante Inhibition und f ur die Repr asentation von Kontrastinformation in zwei komplement aren Dom anen. Basierend auf diesen Ergebnissen stellen wir die Hypothese auf, dass dominante opponente Inhibition im visuellen System verwendet wird, um in verrauschten Umgebungen Kontraste robust extrahieren zu k onnen. Summary. In the primary visual pathway, information is represented in two distinct, complementary domains, namely "on" and "off" cells. In this work we examine how on and off cells may interact to form the input to simple cell subfields. On the basis of physiological evidence, we propose a mechanism of dominating opponent inhibition, where a simple cell subfield is driven by both on and off domains, receiving more heavily weighted input from the opponent pathway. We demonstrate that the model can account for physiological data on luminance gradient reversal recorded from simple cells in cat striate c

A neural model is developed to probe how corticogeniculate feedbackmay contribute to the dynamics of binocular vision. Feedforward and feedbackinteractions among retinal, lateral geniculate, and cortical simple and complex cells are used to simulate psychophysical and neurobiological data concerning the dynamics of binocular disparity processing, including correct registration of disparity in response to dynamically changing stimuli, binocular summation of weak stimuli, and fusion of anticorrelated stimuli when they are delayed, but not when they are simultaneous. The model exploits dynamic rebounds between opponent ON and OFF cells that are due to imbalances in habituative transmitter gates. It shows how corticogeniculate feedback can carry out a top-down matching process that inhibits incorrect disparity responses and reduces persistence of previously correct responses to dynamically changing displays.

Contours and surfaces are basic qualities which are processed by the visual system to aid the successful behavior of autonomous beings within the environment. There is increasing evidence that the two modalities of contours and surfaces are processed in separate, but interacting visual streams or sub-systems. Neurons at early stages in the visual system show strong responses only at locations of high contrast, such as edges, but only weak responses within homogeneous regions. Thus, for the processing and representation of surfaces, the visual system has to integrate sparse local measurements into a dense, coherent representation.