Abstract book (pdf) - ICPR 2010

The goal of this paper is the development of a novel approach for the problem of Noise Removal, based on the theory of
Reproducing Kernels Hilbert Spaces (RKHS). The problem is cast as an optimization task in a RKHS, by taking advantage
of the celebrated semi parametric Representer Theorem. Examples verify that in the presence of gaussian noise the proposed
method performs relatively well compared to wavelet based techniques and outperforms them significantly in the presence
of impulse or mixed noise.
13:50-14:10, Paper WeBT4.2
Multichannel Image Regularisation using Anisotropic Geodesic Filtering
Grazzini, Jacopo, Los Alamos National Lab.
Soille, Pierre, Ec. Joint Res. Centre
Dillard, Scott, Los Alamos National Lab.
This paper extends a recent image-dependent regularisation approach introduced in [Grazzini and Soille, PR09&CCIS09]
aiming at edge-preserving smoothing. For that purpose, geodesic distances equipped with a Riemannian metric need to be
estimated in local neighbourhoods. By deriving an appropriate metric from the gradient structure tensor, the associated geodesic
paths are constrained to follow salient features in images. Following, we design a generalised anisotropic geodesic
filter, incorporating not only a measure of the edge strength, like in the original method, but also further directional information
about the image structures. The proposed filter is particularly efficient at smoothing heterogeneous areas while preserving
relevant structures in multichannel images.
14:10-14:30, Paper WeBT4.3
Local Jet based Similarity for NL-Means Filtering
Manzanera, Antoine, ENSTA-ParisTech
Reducing the dimension of local descriptors in images is useful to perform pixels comparison faster. We show here that, for
computing the NL-means denoising filter, image patches can be favourably replaced by a vector of spatial derivatives (local
jet), to calculate the similarity between pixels. First, we present the basic, limited range implementation, and compare it with
the original NL-means. We use a fast estimation of the noise variance to automatically adjust the decay parameter of the
filter. Next, we present the unlimited range implementation using nearest neighbours search in the local jet space, based on
a binary search tree representation.
14:30-14:50, Paper WeBT4.4
Image Denoising based on Fuzzy and Intra-Scale Dependency in Wavelet Transform Domain
Saeedi, Jamal, Amirkabir Univ. of Tech.
Moradi, Mohammad Hassan, Amirkabir Univ. of Tech.
Abedi, Ali, Amirkabir Univ. of Tech.
In this paper, we propose a new wavelet shrinkage algorithm based on fuzzy logic. Fuzzy logic is used for taking neighbor dependency and
uncorrelated nature of noise into account in wavelet-based image denoising. For this reason, we use a fuzzy feature for enhancing wavelet coefficients
information in the shrinkage step. Then a fuzzy membership function shrinks wavelet coefficients based on the fuzzy feature. We
examine our image denoising algorithm in the dual-tree discrete wavelet transform, which is the new shiftable and modified version of discrete
wavelet transform. Extensive comparisons with the state-of-the-art image denoising algorithm indicate that our image denoising algorithm
has a better performance in noise suppression and edge preservation.
14:50-15:10, Paper WeBT4.5
Noise-Insensitive Contrast Enhancement for Rendering High-Dynamic-Range Images
Lin, Hsueh-Yi Sean, Lunghwa Univ. of Science and Tech.
The process of compressing the high luminance values into the displayable range inevitably incurs the loss of image contrasts. Although the
local adaptation process, such as the two-scale contrast reduction scheme, is capable of preserving details during the HDR compression
process, it cannot be used to enhance the local contrasts of image contents. Moreover, the effect of noise artifacts cannot be eliminated when
the detail manipulation is subsequently performed. We propose a new tone reproduction scheme, which incorporates the local contrast enhancement
and the noise suppression processes, for the display of HDR images. Our experimental results show that the proposed scheme is
indeed effective in enhancing local contrasts of image contents and suppressing noise artifacts during the increase of the visibility of HDR
scenes.
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