D. Sheppard, K. Panchapakesan, A. Bilgin, B. Hunt, M. Marcellin
{"title":"Removal of image defocus and motion blur effects with a nonlinear interpolative vector quantizer","authors":"D. Sheppard, K. Panchapakesan, A. Bilgin, B. Hunt, M. Marcellin","doi":"10.1109/IAI.1998.666850","DOIUrl":null,"url":null,"abstract":"In this paper, results are presented which demonstrate the removal of image defocus and motion blur effects using an algorithm based on nonlinear interpolative vector quantization (NLIVQ). The algorithm is trained on original and diffraction-limited image pairs which are representative of the class of images of interest. The discrete cosine transform is used in the code-book design process to control complexity. Imagery processed with this algorithm demonstrate both qualitative and quantitative improvements (as measured by the peak signal-to-noise-ratio before and after processing).","PeriodicalId":373701,"journal":{"name":"1998 IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No.98EX165)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1998-04-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"1998 IEEE Southwest Symposium on Image Analysis and Interpretation (Cat. No.98EX165)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IAI.1998.666850","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 10
Abstract
In this paper, results are presented which demonstrate the removal of image defocus and motion blur effects using an algorithm based on nonlinear interpolative vector quantization (NLIVQ). The algorithm is trained on original and diffraction-limited image pairs which are representative of the class of images of interest. The discrete cosine transform is used in the code-book design process to control complexity. Imagery processed with this algorithm demonstrate both qualitative and quantitative improvements (as measured by the peak signal-to-noise-ratio before and after processing).