Abstract book (pdf) - ICPR 2010

Optimal sharpness differs from image to image, de-pending on the content. In general, human observer prefers images of
artifacts sharper and those of natural-objects less sharper. We have developed a content-adaptive automatic image sharpening
algorithm that relies on the length of lines extracted from the image. It is applicable to images with various regions
such as those contain natural and artificial objects. The proposed algorithm is expected to be used in image processing
modules of image input/output devices, e.g. digital cameras, printers, etc.
09:00-11:10, Paper WeAT8.5
Irradiance Preserving Image Interpolation
Giachetti, Andrea, Univ. di Verona
In this paper we present a new image up scaling (single image super resolution) algorithm. It is based on the refinement
of a simple pixel decimation followed by an optimization step maximizing the smoothness of the second order derivatives
of the image intensity while keeping the sum of the brightness values of each subdivided pixel (i.e. the estimated irradiance
on the area) constant. The method is physically grounded and creates images that appear very sharp and with reduced artifacts.
Subjective and objective tests demonstrate the high quality of the results obtained.
09:00-11:10, Paper WeAT8.7
Interpolation and Sampling on a Honeycomb Lattice
Strand, Robin, Uppsala Univ.
In this paper, we focus on the three-dimensional honeycomb point-lattice in which the Voronoi regions are hexagonal
prisms. The ideal interpolation function is derived by using a Fourier transform of the sampling lattice. From these results,
the sampling efficiency of the lattice follows.
09:00-11:10, Paper WeAT8.8
Optimization of Topological Active Models with Multiobjective Evolutionary Algorithms
Novo Buján, Jorge, Varpa group, Univ. of A Coruña
Santos, Jose, Univ. of A Coruña
Gonzalez Penedo, Manuel Francisco, Univ. of A Coruña
Fernández Arias, Alba, VARPA Group, Univ. of A Coruña
In this work we use the evolutionary multiobjective methodology for the optimization of topological active models, a deformable
model that integrates features of region-based and boundary-based segmentation techniques. The model deformation
is controlled by energy functions that must be minimized. As in other deformable models, a correct segmentation
is achieved through the optimization of the model, governed by energy parameters that must be experimentally tuned.
Evolutionary multiobjective optimization gives a solution to this problem by considering the optimization of several objectives
in parallel. Concretely, we use the SPEA2 algorithm, adapted to our application, the search of the Pareto optimal
individuals. The proposed method was tested on several representative images from different domains yielding highly accurate
results.
09:00-11:10, Paper WeAT8.9
Fast Super-Resolution using Weighted Median Filtering
Nasonov, Andrey, Lomonosov Moscow State Univ.
Krylov, Andrey S., Lomonosov Moscow State Univ.
A non-iterative method of image super-resolution based on weighted median filtering with Gaussian weights is proposed.
Visual tests and basic edges metrics were used to examine the method. It was shown that the weighted median filtering
reduces the errors caused by inaccurate motion vectors.
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