Volume 1 No2 April 2007
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| 1. |
A New Adaptive Class of Filter Operators for Salt & Pepper Impulse Corrupted Images Download PDF |
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Authors |
Krishnan Nallaperumal, Justin Varghese, S. Saudia, Santhosh. P. Mathew, K. Krishnaveni, P. Kumar |
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Abstract |
The paper proposes two new adaptive filtering algorithms for the restoration of salt & pepper impulse corrupted digital images; the Iterative Adaptive Switching Median Filter(IASMF) and the Adaptive Threshold based Median Filter(ATMF). The IASMF works steadily on the corrupted pixels of the noisy image degraded at all noise ratio whereas ATMF works on highly corrupted environments to give acceptable outputs of better visual quality. Experimental results show that the proposed adaptive filters give enhanced subjectiveness and objectiveness in restoring images than many other impulse filters whose outputs show black and white patches with blurred effects at higher noise levels. They are also computationally efficient than many other reputed impulse filters, the ATMF a slightly complex due to its pixel-wise comparison with the valid median. |
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Keywords |
Adaptive filter, image restoration, impulse detection, impulse noise, median filter, pseudo median. |
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| 2. |
Adaptive Switching Rank-ordered Impulse Noise Filters: New Techniques, Results and Analysis Download PDF |
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Authors |
Justin Varghese |
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Abstract |
Two new adaptive switching rank-ordered impulse noise filters are proposed for the restoration of digital images corrupted by salt & pepper impulse noise: the Adaptive Switching Median Filter (ASMF) and the Adaptive Rank order based Switching Median Filter (ARSMF). The ASMF implemented by a two pass algorithm for impulse detection and impulse correction is an efficient filtering technique that works on to give consistent subjectiveness and objectiveness on images corrupted at low or high noise ratios whereas the computationally powerful ARSMF is more suitable for highly corrupted images. They identify the noisy pixels and replace them by a much valid intensity from the smallest possible neighborhood and keep up the image fidelity to a large extent. Experimental results and simulation analysis show that the proposed ASMF and ARSMF algorithms perform far more superior than many of the median filtering techniques including the top-ranking impulse Filters, the Progressive Switching Median Filter, the Rank order based Median Filter. The restored outputs are free from patchy effects, does not extend black or white blocks in the image. |
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Keywords |
Adaptive filter, image restoration, impulse detection, impulse noise, median filter, pseudo median. |
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| 3. |
A novel Multi-scale Morphological Watershed Segmentation Algorithm Download PDF |
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Authors |
Krishnan Nallaperumal, K.Krishnaveni, Justin Varghese, S. Saudia, S. Annam, P. Kumar |
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Abstract |
A novel segmentation algorithm is proposed in this paper for digital image segmentation. The specialized pre-processing set-up completely restores even the impulse corrupted images and generates all the information required for perfect segmentation. The algorithm works on the marker extractions of the gradient images obtained by multiscale morphological reconstruction and avoids oversegmentation vivid in Watershed algorithm. Experimental results add to the computational efficiency, shape maintaining, edge preserving and scale-calibrating features of the algorithm. The performance is also superior to most other standard segmentation algorithms. |
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Keywords |
Digital image segmentation. |
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| 4. |
Markov Chain Monte Carlo Methods in Molecular Computing Download PDF |
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Authors |
Kaliaperumal Senthamarai Kannan, Velusamy Vallinayagam, Perumal Venkatesan |
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Abstract |
The core data of molecular biology consists of DNA sequences. Molecular computation focuses on the computational power of molecules, especially that of biological molecules, and attempts to realize information processing which maximally exploits the computational power of molecules. DNA sequences can hold information of arbitral complexity by freely chaining four natural bases. Similarly, biological molecules such as RNA and proteins are appropriate for molecular computation, because they share this combinatorial complexity. It is worth mentioning that the combinatorial complexity underlies the complexity of life. This paper discusses the applications of MCMC in molecular computing. |
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Keywords |
Markov Chain Monte Carlo, Molecular computing, genome, DNA, Bayesian, similarity. |
