Showing papers on "Human visual system model published in 1973"

Image-detector model and parameters of the human visual system.

Abstract: An image-detector model of the visual system is described. Analysis of detection-probability data combined with signal-to-noise analysis of contrast-sensitivity data yield the fundamental visual-system parameters required to predict image-detection performance. The results for background luminances ranging from 10−3 to 102 millilamberts include the values of the threshold detection criterion or signal-to-noise ratio, the response time, the effective responsive quantum efficiency, the effective angular width of the point spread function, and the effective angular width of the maximum photoreceptor field belonging to the minimum-bandwidth spatial filter. Excellent agreement between theoretical curves and experimental data is shown.

Analysis of Noise-Required Contrast and Modulation in Image-Detecting and Display Systems

Abstract: The purpose of an electrooptical display system is to convert electrical messages into luminous messages for transmittal to the retina of the eye. In the retina photodetection occurs and the signal processing is initiated which, continued in the brain, permits the observer to make decisions based on the acquired visual sensory information. The overall performance of this display-observer system is measured by the probability of the observer making a correct decision in a given visual task. Clearly the overall performance depends on the interaction between the parameters of the display and eye and on the parameters of the human visual system as well as on the parameters of the display itself. Therefore the choice of display design parameters to ensure optimum overall performance depends on a clear understanding of the operation of the visual sensory system and the interaction between it and the display.

The use of a priori knowledge in image processing

Abstract: The processing of images on a digital computer is usually done for the purpose of extracting information from an image which the unaided human visual system cannot extract by itself. In nearly all image processing procedures a large amount of a priori knowledge related to the image must be utilized in order to extract the desired information. By a priori knowledge we mean knowledge about the image obtained from sources other than the image itself. This knowledge might include information about the object, the transmission media, the optical system, the sensor, the scanning and digitizing equipment, and the processing technique. Often a part of the a priori knowledge is contained in the mind of the observer as a result of accumulated experience.