Showing papers on "Human visual system model published in 1975"

Computer simulations of a dynamic visual perception model

Abstract: The human visual system must operate in a rapidly changing environment, as objects, eyes and observer are continually moving. This fact must, to a great extent, determine how the system analyses its retinal input. We argue that perception should be regarded as a dynamic process in which patterns of neural activity are developed and change in ways which reflect changes in the visual field. A model is described to suggest how the visual system may keep track of perceived objects as their images move on the retina. We postulate that at some level of the visual system, the position of these objects relative to the observer is represented by a pattern of neural activity. Such a pattern of activity must move as a unit as the object it represents moves: the pattern cannot be continually regenerated during motion. In the model we propose, information is represented by activity in two-dimensional, homogeneous layers of neuron-like elements. A number of these layers are arranged in parallel, and activity within separate layers represents object position and the components of retinal image velocity due to object and observer motion. Object velocity, which cannot be directly sensed at the level of the retina, is isolated and represented analogically. This representational isolation of object- and observer-related velocity allows us to explain several illusions of motion perception, including induced motion and the “waterfall effect”.

Processing of positional information in the human visual system

Abstract: CONTOURS seem to be shifted away from the edge of a previously seen figure. Ganz1 considered this apparent displacement to be caused by lateral inhibition between the contours of an after image of the inducing figure and the test figure itself.

Visual construction of color is digital

Abstract: When disparate shapes are flashed under the appropriate temporal and spatial conditions, the human visual system resolves their disparity smoothly and continuously. No equivalent supplementations are found for color, which the system resolves by abrupt transformation. Shape and color reveal themselves, contrary to some modern theorizing, as properties handled in different ways by the visual nervous system, continuous or analog for shape, abrupt or digital for color.

Analog optical block processor

Abstract: Light quantization of elemental areas of pictorial information by a plurality of contiguous light integrating tunnels, either with or without one of a group of different sampling-function array masks and/or printing-function array masks, is used to modify the original picture information for such purposes as subjectively providing a (1) more pleasing picture, (2) striking special display effects and (3) studying visual perception by the human visual system. Analog processor replaces expensive computer equipment which also required tedious programming, formerly required for producing similar modification of picture information.

Hardware for visual image processing

Abstract: Emphasis in this survey of hardware for visual image processing is on centers which specialize in "computer vision" research, although some of the findings are generally applicable to all areas of image processing. Tradeoffs between parameters of speed, dynamic range, and resolution are discussed as they apply to industrial and research applications. A discussion of various types of imaging devices and analog-to-digital converters follows. Next, problems which occur in various devices are discussed and some methods of compensation are suggested. Then, the three most popular methods of computer entry of image data are compared. The paper concludes with a brief description of visual image processing research in progress at nine laboratories, with emphasis on the hardware used by those laboratories as it relates to the problems being worked on.

Image Processing in the Human Visual System.

Abstract: : This work extends the multiplicative visual model to include image texture as suggested by previous experiments linking a low resolution Fourier analysis with neurons in certain parts of the visual cortex. The new model takes image texture into account in the sense that weak texture is accentuated and strong, high contrast texture is attenuated. This model is then used as the basis for an improved image enhancement scheme and an unusually successful method for restoring blurred images. In addition, it is suggested how the model may provide new insights into the problem of finding a quantitatively correct image fidelity criterion. The structure of this model is described in relation to visual neurophysiology and examples are presented of images processed by the new techniques. The present research also shows how Land's 'retinex' can be implemented in a new way which allows the required computations to be carried out on a rectangular grid.

Image Transmission and Coding Based on Human Vision.

Abstract: : In recent years more and more attention was paid to digital image processing especially as a result of the development of highly efficient algorithms and also because of technologically better facilities. Concurrently attempts were made to find a mathematical model for human vision to achieve better understanding about that mechanism. Some of the image processing problems that were (and are) tackled are image enhancement, bandwidth reduction, image transmission, etc. Unfortunately very few have taken the mechanism of the human vision into consideration in their processes. This work is an attempt to incorporate the model of human vision in image transmission and coding. An optimal system is developed to transmit a digital image over a noisy channel. The same system is used for image bandwidth reduction utilizing a simple coding scheme which is not based on the knowledge of the statistics of the image in question. The improvement of the optimal system over other similar systems are demonstrated and provide explanation for situations where other systems failed. The model used for transmitting images can be also interpreted as the model of the visual mechanism itself and thus shed some light on human vision from a new interesting aspect.

An hypothesis-driven vision system

Abstract: This paper presents a small vision system created to study Minsky's theory of Frame Systems It is organized around a detailed semantic hypothetical model of the scene, which is capable of being structurally altered and adjusted to fit the visual data. Visual data is gathered through a window, whose position is controlled by suggestions which arise from uncertain parameters of the hypothetical model.

Work of the human visual system. I. Adequate visual stimulus

Abstract: It is shown that the adequate stimulus permitting to detect the presence of colour differentiation in the visual field is the change of relative space-time differences of light actions in different retinal points. Differences only in space or only in time are not sufficient for perception.

Work of the human visual system. II. Color

Abstract: In the first part of this work [1] the author presented the expression for so called adequate visual stimulus. This expression describing the change of relative space - time differences of light actions in different retinal points defines the conditions necessary for producing visual sensations. In this paper author makes a statement that the quality of visual sensation (the percieved colour) can be evaluated by integrating the expression for the adequate visual stimulus both in time and in space. The integration in space is fulfilled starting from the extreme periphery of the retina, which is usually illuminated by scattered light averaged over the whole visual field. Human visual system works in such a way that the light action in the extreme periphery plays a role of the unit for scaling of visual sensations.

Quasi-real time improvement in small format images

Abstract: A novel image processing technique simulating mechanisms of the human visual system is described. An experiment is detailed, applying the principles of this technique to the digital manipulation of a defocused 35 mm image, and shows the spatial frequency improvement in the resolution of a processed image over the original. The design of a quasi-real time electronic system to rapidly process degraded images in quick succession is discussed.

An Overview Of Human Observer Characteristics And Their Effect On Image Transmission And Display

Abstract: AN OVERVIEW OF HUMAN OBSERVER CHARACTERISTICS AND THEIR EFFECTON IMAGE TRANSMISSION AND DISPLAYThomas G. Stockham, Jr.Departments of Computer Science and Electrical EngineeringUniversity of UtahSalt Lake City, Utah 84112The science and technology of image transmission and display has evolved primarilyfrom the diciplines of computer science, electrical engineering and physics. Thus, it isonly natural that techniques and attitudes which have developed are characterized by thestyle in which people in these areas approach the subject of images and their trans-mission, display, and processing. For example, one finds many important differencesbetween the methods of television and those of photography. Moreover, an even greatercontrast is found when comparing the methods of electrical engineering, physics, tele-vision and photography with those now understood to be employed by the human eye and thehuman visual system. Specifically, let us contrast the method by which television,photography and the human visual system, represent image information. In television(particularly digital imaging), image values are represented by signals analogous toquantities of light. They are called intensities. In photography, on the other hand,the representing quantities are concentrations of silver or dyes. Consequently, due tothe natural exponentiating laws governing the interaction of light with these media,they are analogous to the logarithm of quantities of light. They are called densities.The human visual system, on the other hand, (while being generally logarithmicallysensitive) moves a large step further away from representation by physical quantities oflight and produces at very early stages in its processing highly modified versions of thepatterns of light or their logarithms. The natural question then arrises, why should thehuman visual system try to do this; and since it does, what consequences are implied interms of the television and photographic presentations normally employed?The answers to these questions rest crucially on the issue of errors. In any trans-mission or display system, errors will be committed. These are unavoidable and are aresult of the physical limitations encountered. In a broad variety of applications, themost important forms of error encountered are those imposed by limited dynamic range andvarious forms of noise. The classic dilemma one faces in the diciplines of image trans-mission and display is that a compromise must be effective between the conflicting con-straints of dynamic range and noise. On the one hand, one wishes to make signals largerso that the noise may be rendered negligible. At the same time, large signals are pre-cluded by the limitation in dynamic range in the form of distortions which effect thesignals when their values are made too variable. More specifically, in any transmissionand /or display design, the natural goal would seem to be the attainment of fidelityreproduction. Unfortunately, the demands of typical imagery upon transmission and dis-play systems is usually so severe that this goal cannot be reasonably met. The dis-tortions due to limited dynamic range and noise, especially the former, are relentlesslyunavoidable and so the designer must content himself with one form of distortion oranother.Fortunately, the human visual system itself produces a large quantity of distortion.This phenomenon may be exploited by trading off undesirable forms for forms which will beencountered naturally anyway. The distortions produced by the human visual system areoften referred to as optical illusions. The simplest of these is the gray scale illusionwhich reveals the logarithmic sensitivity of the human visual system alluded to above(1).This illusion is responsible for the fact that we do not turn the lights on during theday although they add just as much light then as at night. Another ramification is thatgray scales must be arranged in exponential progression to appear arithmetic to theobserver.Other illusions which are spatial in character are much more important and striking,however. The simplest of these is the illusion of simultaneous contrast which permitstwo neutral gray shades to appear so different from one another at the same time, thatone can assign the names near -white to one and near -black to the other. Careful study ofthese illusions has permitted researchers to formulate signal processing models for theearly processing stages of the human visual system. These models (e.g. consider those ofStockham(2), Baudelaire(3), Frei(4), and Baxter(5)) predict the human visual illusions ordistortions well enough to permit their use in defining useful objective measures of howdifferent two images (one original, the other distorted) will look from one another.Applications of these models to problems in image transmission and display havealready yielded significant advantages. For example, when the model is used to evaluatethe distortions produced by a given display instrument, it is often possible to predicthow the physical performance of that display may be significantly relaxed without

Identification Thresholds of the Human Visual System for an Alphanumeric Resolution Test Object

Abstract: Many investigations of the detection threshold of the human visual system have been conducted, and a few recognition threshold studies can be found, however no identification threshold data are available. This paper documents research on the observer's identification threshold for an alphanumeric resolution test object presented at various average luminance levels, contrasts, and contrast polarities. These factors affected the identification threshold in a similar way to the effects they exert on the observer's detection and recognition thresholds; the test object contrast being the most significant factor. Direct numerical comparisons between the various thresholds were not possible due to the large inherent differences between the test object visual task complexities found in the many threshold investigations.

A Pattern Processing Model of the Human Visual System

Abstract: Basically there are two approaches to simulation The first type involves the analysis of the “real” system, so as to identify the critical processes performed by the system The second type is not concerned at all with the processes performed by the “real” system but is solely interested in the input and output of the system The objective of this presentation is to introduce a model of the human visual system, based upon the first form of simulation More specifically, the model is directed toward the pattern recognition, discrimination, and classification processes of the human visual system