1 June 1991 Image quality measurements with a neural brightness perception model
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Abstract
A computational model for the human perception of image brightness has been advanced by Cohen, Grossberg, and Todorovic. The research describes how this model can be used to assess perceived image quality. The implementation of the model is extended to allow the processing of larger images and an increased dynamic range of the gray scale. The model is validated by examining the simulation of some classical brightness perception phenomena including the Herman grid illusion, and the Craik-O'Brien-Cornsweet effect. Results of a comparative evaluation of three halftoning algorithms are offered which indicate that the model is useful for the evaluation of image processing algorithms. Human subjects ranked the quality of the images halftoned with each of three different algorithms at three different viewing distances. Objective measures of the halftoned images were obtained after preprocessing to account for the different viewing distances. The ranking of the objective measures did not correspond to those of the majority of the human observers. However, after processing by the brightness perception model, ranking of the objective measures do correspond with the rankings assigned by human observers.
© (1991) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Timothy A. Grogan, Timothy A. Grogan, Mei Wu, Mei Wu, } "Image quality measurements with a neural brightness perception model", Proc. SPIE 1453, Human Vision, Visual Processing, and Digital Display II, (1 June 1991); doi: 10.1117/12.44341; https://doi.org/10.1117/12.44341
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