A blind deconvolution algorithm based on the Richardson -Lucy deconvolution algorithm is presented. Its performance in the presence of noise is found to be superior to that of other blind deconvolution algorithms. Results are presented and compared with results obtained from implementation of a Weiner filter blind deconvolution algorithm. The algorithm is developed further to incorporate functional forms of the pointspread function with unknown parameters. In the presence of noise the point-spread function can be evaluated with 1.0% error, and the object can be reconstructed with a quality near that of the deconvolution process with a known point-spread function.

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This study was concerned with the question of which personality variables are most predictive of judgements of particular types of painting. One hundred and twenty-one participants rated 24 slides of abstract, pop art, and representational paintings. They then completed two questionnaires which measured sensation seeking (SS) and the`Big Five' personality dimensions. Thrill and Adventure Seeking was positively correlated with a liking of representational art while Disinhibition was associated with positive ratings of abstract art and pop art. Neuroticism was positively correlated with positive ratings of abstract and pop art, while conscientiousness was linked to liking of representational art. Openness to Experience was linked to positive ratings of all three art types. Agreeableness was negatively linked to liking of pop art. It was also found that art education and frequency of visits to art galleries were linked to positive ratings of abstract paintings. Regressional analyses showed about a ®fth of the variance could be accounted for by personality and demographic variables. Personality variables were most strongly linked to positive judgements of representational art and least related to ratings of pop art. Overall the sensation seeking variables accounted for more of the variance than the big ®ve dimensions.

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