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 Behnaz Pirzamanbein . Photo

Behnaz Pirzamanbin

Associate senior lecturer

 Behnaz Pirzamanbein . Photo

Modulus of continuity and its application in classifying the smoothness of images.

Author

  • Behnaz Pirzamanbein

Summary, in English

The problems of de-blurring, de-noising, compression and segmentation are fundamental problems in image processing. Each of these problems can be formulated as a problem to find some approximation of an initial image. To find this approximation one needs to specify the approximation space and in what space the error between the image and its approximation should be calculated.

Using the space of Bounded Variation, BV, became very popular in the last decade. However it was later proved that for a rich variety of natural images it is more effective to use spaces of smooth functions that arecalled Besov spaces instead of BV. In the previous papers two methods for classifying the smoothness of images were suggested. The DeVore’s method based on the wavelet transform and Carasso’s method based on singular integrals are reviewed.

The classical definition of Besov spaces is based on the modulus of continuity. In this master thesis a new method is suggested for classifying the smoothness of images based on this definition. The developed method was applied to some images to classify the smoothness of them.

Publishing year

2011

Language

English

Document type

Master's Thesis

Publisher

Linnaeus University

Topic

  • Mathematical Analysis

Status

Published