Showing papers by "Bogdan Smolka published in 2001"

On the reduction of impulsive noise in multichannel image processing

Abstract: A new approach to the problem of impulsive-noise reduction for color images is introduced. The major advantage of the technique is that it filters out the noise component while adapting itself to the local image structures. In this way the algorithm is able to eliminate strong impulsive noise while preserving edges and fine image details. As the algorithm is a fuzzy modification of the commonly used vector median operator, it is very fast and easy to implement. Our results show that the proposed method outperforms all standard algorithms for the reduction of impulsive noise in color images. © 2001 Society of Photo-Optical Instrumenta- tion Engineers. (DOI: 10.1117/1.1367347)

Fast Modified Vector Median Filter

Abstract: A new filtering approach designed to eliminate impulsive noise in color images, while preserving fine image details is presented in this paper. The computational complexity of the new filter is significantly lower than that of the Vector Median Filter. The comparison shows that the new filter outperforms the VMF, as well as other standard procedures used in color image processing, when the impulse noise is to be eliminated.

On the fast modified vector median filter

Abstract: A new filtering approach designed to eliminate impulsive noise in color images, while preserving fine image details is presented in this paper. The computational complexity of the new filter is lower than that of the vector median. The comparison shows that the new filter outperforms the VMF, as well as other standard procedures used in color image processing, when the impulse noise is to be eliminated.

Random Walk Approach to Noise Reduction in Color Images

Abstract: In this paper we propose a new algorithm of noise reduction in color images. The new technique of image enhancement is capable of reducing impulsive and Gaussian noise and it outperforms the standard methods of noise reduction. In the paper a smoothing operator, based on a random walk model and on a fuzzy similarity measure between pixels connected by a digital self avoiding path is introduced. The efficiency of the proposed method was tested on the test color image using the objective image quality measures and the results show that the new method outperforms standard noise reduction algorithms.

On the segmentation of the Comet Assay images

Abstract: The single cell gel electrophoresis, called Comet Assay is a microelectrophoretic technique of direct visualization of DNA damage at the cell level. In the comet assay, the cells suspended in an agarose gel on a microscope slide are subjected to lysis, unwinding of DNA and electrophoresis. After staining with fluorescent DNA binding dye, cells with DNA damage display increased migration of genetic material from the cell nucleus. Under the influence of weak, static electric field, charged DNA migrates away from the nucleus forming a so called comet. The damage is quantified by measuring the amount of the genetic material, which migrates from the nucleus to form the comet tail. The foremost advantage of the comet assay is that it analyses individual cells, thus allowing the measurement of the heterogeneity of response within a cell population. In this paper we present three novel methods of the comet tail and head extraction.

On the new filtering technique of noise attenuation in color images

Abstract: A new filter class for multichannel image processing is introduced and analyzed. The new technique of image enhancement is capable of reducing impulsive and Gaussian noise and it significantly outperforms the standard methods of noise reduction. In the paper, a smoothing operator, based on a random walk model and on a fuzzy similarity measure between pixels connected by a digital geodesic path, is introduced. The efficiency of the proposed method was tested on standard color images using objective image quality measures. Obtained results show that the new method not only outperforms standard noise reduction algorithms, but has some interesting features useful for segmentation of noisy color images.

On a new class of filters for the impulsive noise reduction in color images

Abstract: In this paper, a new approach to the problem of impulsive noise reduction for color images is presented. The new image filtering technique is based on the maximization of the similarities between pixels in a predefined filtering window. The new method filters out the noise component, while adapting itself to the local image structures. In this way, the proposed algorithm is able to eliminate impulsive noise, while preserving edges and fine image details. Since the algorithm can be considered as a vector median filter driven by fuzzy membership functions, it is fast and computationally efficient. Experimental results indicate that the proposed filter outperforms other commonly used algorithms for impulsive noise reduction in color images.

On the efficiency of random walk approach to noise reduction in color images

Abstract: We propose a new algorithm of noise reduction in color images. The new technique of multichannel image enhancement is capable of reducing impulse and Gaussian noise and it outperforms the basic methods based on vector median used for noise reduction in color images. A new smoothing operator, based on a random walk model and on a fuzzy similarity measure between pixels connected by a digital geodesic path is introduced. The efficiency of the proposed method was tested on the standard color images using the widely used objective image quality.