Study of the human recognition of images to evaluate current performance measures
Autor: | Kevin St. John Murphy, Alison M. Fairhurst, Alan H. Lettington |
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Rok vydání: | 1995 |
Předmět: |
business.product_category
Observer (quantum physics) Image quality business.industry Computer-generated imagery Gaussian media_common.quotation_subject Detector symbols.namesake Geography Sampling (signal processing) symbols Contrast (vision) Computer vision Artificial intelligence Computer monitor business media_common |
Zdroj: | SPIE Proceedings. |
ISSN: | 0277-786X |
DOI: | 10.1117/12.210048 |
Popis: | Current performance measures for thermal imagers relate only indirectly to human recognition. However, as the probability of recognizing an image may be used as a measure of image quality, the relationship described in this work could contribute to the formation of a new objective performance measure for thermal imaging systems. The human recognition probabilities of several degraded shapes have been evaluated using computer generated images displayed on a computer monitor. The shapes investigated were blurred by convolving them with a range of two dimensional Gaussian functions. In subsequent trials, these blurred images were further degraded by sampling (in order to simulate the effect of detector arrays in an imager). Images of degraded shapes were presented to observers in a random order and with a random degradation. After each presentation the observer decided which was the most likely shape to represent the image displayed on the screen. A correlation has been found between the probability of recognition of a particular degraded shape and the relative contrast between the image of that shape and a similarly degraded circle of the same area. This is true whether the degradation is due to blurring alone or to blurring followed by sampling.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only. |
Databáze: | OpenAIRE |
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