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Modulus of continuity and its application in classifying the smoothness of images.
Linnaeus University, Faculty of Science and Engineering, School of Computer Science, Physics and Mathematics.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

The problems of de-blurring, de-noising, compression and segmenta-

tion are fundamental problems in image processing. Each of these prob-

lems can be formulated as a problem to find some approximation of an

initial image. To find this approximation one needs to specify the ap-

proximation 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 nat-

ural images it is more effective to use spaces of smooth functions that are

called 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.

Place, publisher, year, edition, pages
2011. , 53 p.
URN: urn:nbn:se:lnu:diva-12313OAI: diva2:421982
Subject / course
Available from: 2011-06-10 Created: 2011-06-10 Last updated: 2011-06-10Bibliographically approved

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