Relating Statistical Image Differences and Degradation Features

Elisa Barney Smith, Boise State University
Xiaohui Qiu, Nanjing University of Post and Telecommunication

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This is an author-produced, peer-reviewed version of this article. The final publication is available at www.springerlink.com. Copyright restrictions may apply. DOI: 10.1007/3-540-45869-7_1

Abstract

Document images are degraded through bilevel processes such as scanning, printing, and photocopying. The resulting image degradations can be categorized based either on observable degradation features or on degradation model parameters. The degradation features can be related mathematically to model parameters. In this paper we statistically compare pairs of populations of degraded character images created with different model parameters. The changes in the probability that the characters are from different populations when the model parameters vary correlate with the relationship between observable degradation features and the model parameters. The paper also shows which features have the largest impact on the image.