Bogdan Smolka

Vector filtering for color imaging

Vector processing operations use essential spectral and spatial information to remove noise and localize microarray spots. The proposed fully automated vector technique can be easily implemented in either hardware or software; and incorporated in any existing microarray image analysis and gene expression tool.

Fast detection and impulsive noise removal in color images

In this paper, a novel approach to the impulsive noise removal in color images is presented. The proposed technique employs the switching scheme based on the impulse detection mechanism using the so-called peer group concept. Compared to the vector median filter and other commonly used multichannel filters, the proposed technique consistently yields very good results in suppressing both the random and fixed-valued impulsive noise. The main advantage of the proposed noise detection framework is its enormous computational speed, which enables efficient filtering of color images in real-time applications.

Self-adaptive algorithm of impulsive noise reduction in color images

In this paper a new approach to the problem of impulsive noise reduction in color images is presented. The basic idea behind the new image filtering technique is the maximization of the similarities between pixels in a predefined filtering window. The improvement introduced to this technique lies in the adaptive establishing of parameters of the similarity function and causes that the new filter adapts itself to the fraction of corrupted image pixels. The new method preserves edges, corners and fine image details, is relatively fast and easy to implement. The results show that the proposed method outperforms most of the basic algorithms for the reduction of impulsive noise in color images.

Selection weighted vector directional filters

In this paper, a class of weighted vector directional filters (WVDFs) based on the selection of the output sample from the multichannel input set is analyzed and optimized. The WVDF output minimizes the sum of weighted angular distances to other input samples from the filtering window. Dependent on the weighting coefficients, the class of the WVDFs can be designed to perform a number of smoothing operations with different properties, which can be applied for specific filtering scenarios. In order to adapt the weighting coefficients to varying noise and image statistics, we introduce a methodology, which achieves an optimal trade-off between smoothing and detail preserving characteristics. The proposed angular optimization algorithms take advantage of adaptive stack filters design and weighted median filtering framework. The optimized WVDFs are able to remove image noise, while maintaining excellent signal-detail preservation capabilities and sufficient robustness for a variety of signal and noise statistics.

Fast adaptive similarity based impulsive noise reduction filter

In this paper, we address the problem of impulsive noise reduction in multichannel images. A new class of filters for noise attenuation is introduced and its relationship with commonly used filtering techniques is investigated. The computational complexity of the new filter is lower than that of the vector median filter (VMF). Extensive simulation experiments indicate that the new filter outperforms the VMF, as well as other techniques currently used to eliminate impulsive noise in color images.

Vector sigma filters for noise detection and removal in color images

This paper presents a new adaptive filtering approach capable of detecting and removing impulsive noise in multichan- nel images. The proposed methodology constitutes a powerful unified framework for multichannel signal processing. Robust order-statistic concepts and statistical measure of vectorsdeviation are used in conjunction with different distance measures among multichannel inputs to determine an efficient switching rule between filter output and no filtering (identity operation). The special case of color image filtering is studied as an important example of multichannel signal processing. Simulation studies reported in this paper indicate that the proposed filter class is computationally attractive, has excellent performance, and is able to preserve fine details while suppressing impulsive noise.

cDNA microarray image processing using fuzzy vector filtering framework

This paper presents a novel filtering framework capable of processing cDNA microarray images. The proposed two-component adaptive vector filters integrate well-known concepts from the areas of fuzzy set theory, nonlinear filtering, multidimensional scaling and robust order-statistics. By appropriately setting the weighting coefficients in a generalized framework, the method is capable of removing noise impairments while preserving structural information in cDNA microarray images. Noise removal is performed by tuning a membership function which utilizes distance criteria applied to cDNA vectorial inputs at each image location. The classical vector representation, adopted here for a two-channel processing task, as well as a new color-ratio model representation are used. Simulation studies reported in this paper indicate that the proposed adaptive fuzzy vector filters are computationally attractive, yield excellent performance and are able to preserve structural information while efficiently suppressing noise in cDNA microarray data.

A Statistically-Switched Adaptive Vector Median Filter

Abstract This paper presents a new cost-effective, adaptive multichannel filter taking advantage of switching schemes, robust order-statistic theory and approximation of the multivariate dispersion. Introducing the statistical control of the switching between the vector median and the identity operation, the developed filter enhances the detail-preserving capability of the standard vector median filter. The analysis and experimental results reported in this paper indicate that the proposed method is capable of detecting and removing impulsive noise in multichannel images. At the same time, the method is computationally efficient and provides excellent balance between the noise attenuation and signal-detail preservation. Excellent performance of the proposed method is tested using standard test color images as well as real images related to emerging virtual restoration of artworks.

Sharpening vector median filters

A sharpening vector median (VM) filter for simultaneous denoising and enhancing vector-valued signals is introduced. This filter uses the trimmed aggregated distance minimization concept and robust vector order statistics to enhance edges and image details while retaining the noise removal characteristics of the standard VM operator. The procedure accommodates various design, implementation and application objectives by enhancing the vector-valued signals depending on the local image statistics and/or the users needs. The filter properties discussed in this paper are proven and suggest that the proposed solution is a robust vector processing operator. The performance and efficiency of the filter are analyzed and commented upon. Examples from its application to color image filtering and virtual restoration of artworks are provided.

Peer group switching filter for impulse noise reduction incolor images

In this paper a novel approach to the problem of impulsive noise reduction in color images is presented. The proposed technique is based on the evaluation of the statistical properties of a sorted sequence of accumulated distances used for the calculation of the vector median. The detection of corrupted pixels is performed using the Fishers linear discriminant working on the aggregated distances assigned to each of the pixels from the filtering window. The aim of the discriminant is to divide the pixels into two classes: a peer group of pixels similar to the vector median and a set of pixels consisting of outliers injected into the image by the noise process. The described filter enables reliable detection of impulses and its output switches between the vector median and the original, undisturbed pixel. In order to increase the filters performance, a thresholding scheme is introduced to enhance the detail preserving abilities of the proposed noise attenuation scheme.