From Nataša Sladoje

Main: Research

Research interests

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Coverage Model and its Application to High Precision Image Processing

The coverage model, which we have been developing for several years now, provides a framework for representing objects present in digital images as spatial fuzzy subsets. Assigned membership values indicate to what extent image elements are covered by the imaged objects. During last years, we have shown, both theoretically, and in applications, that the model can be used to improve information extraction from digital images and to reduce problems originating from limited spatial resolution.

People Joakim Lindblad, Slobodan Dražić, Vladimir Ilić, Kristina Lidayova, Zoltan Kato, Attila Tanács

Published results:

Image Restoration Based on Energy Minimization

A common approach to solve the very important but severely ill-posed problem of image deconvolution, is to formulate it in a form of an energy minimization problem. We study performances of energy minimization based restoration methods for enhancing images degraded with blur and different types of noise types - Gaussian, Poisson and mixed Poisson-Gaussian.

People: Buda Bajić, Joakim Lindblad, Tibor Lukić

Published results:

Precise image processing for biomedical and medical applications

Efficient utilization of available image data to achieve sub-pixel/voxel precision and characterize barely resolved structures, or address partial volume effect, is crucial in many biomedical and medical applications. We rely on theoretical work within the framework of discrete mathematics, which provides methods which enable preservation and efficient usage of information, aggregate information of different types, improve robustness of the developed methods and increase precision of the analysis results.

People: Joakim Lindblad, Ewert Bengtsson, Ida-Maria Sintorn, Zoltan Kato, Attila Tanács, Amit Suveer, Anindya Gupta, Patrik Malm, Anca Dragomir, Andrew Mehnert, Ramin Moshavegh

Published results:

Distance measures between objects and images

We study distance measures between sets which can be applied in image processing. We have proposed new distance measures and have evaluated their performance in template matching, and object classification. We are particularly interested in distance which are applicable to information-rich object representations, conveniently modeled by fuzzy sets.

People: Joakim Lindblad, Johan Öfverstedt, Vladimir Ćurić, Gunilla Borgefors

Published results:

Fuzzy spatial sets in image analysis

Fuzzy set theory has found many applications in image processing. I am interested in modeling image objects as spatial fuzzy sets, and developing methods applicable to such representations. This approach shows to provide information preservation and increased precision of feature estimates.

People: Joakim Lindblad, Ingela Nyström, Punam K. Saha, Marija Delić

Published results:

Shape representation and reconstruction

My early interests were representation and reconstruction of binary shapes by geometric moments.

People: Joviša Žunić

Published results:

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