Sunil Bhooshan

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We develop a multiexposure image fusion method based on texture features, which exploits the edge preserving and intraregion smoothing property of nonlinear diffusion filters based on partial differential equations (PDE). With the captured multi-exposure image series, we first decompose images into base layers and detail layers to extract sharp details and(More)
In this paper we propose a new method for companding a discrete signal, by a process we will call by the name of T-Law. When this data is processed according to the discussed technique, it gives much less average quantization noise than both μ and A-laws. The technique proposed requires much less number of calculations when comapared with μ(More)
In this paper an edge coupled microstrip coupler with defected ground structure is presented. A normally 7 dB coupler designed on Alumina substrate is converted into a 3 dB coupler by cutting single rectangular slot in the ground plane encompassing the two transmission lines. Other properties of backward wave coupler remain the same, except for a tighter(More)
This paper proposes a hybrid approach to compression. It incorporates lossy as well as lossless compression. Various parts of image are compressed in either way, depending on the amount of information held in that part. This scheme consists of two stages. In the first stage the image is filtered by a high pass filter to find the areas that have details. In(More)
Electroencephalogram (EEG) is a time varying brain electrical activity, highly sensitive and gives a coarse view of neural activity. It has been used to study cognitive processes and the physiology of the brain. EEG recordings are distorted by physiological and nonphysiological signals causing problems to the clinicians, neuropsychologist and researchers(More)
EEG is the most economical and effective tool for understanding the complex dynamic behavior of the brain and studying its physiological states. In the present work, hierarchical computer aided diagnostic system (HCAD) for classification of normal, ictal and inter-ictal of EEG signals is proposed. In the present work, three different HCAD systems comprising(More)
Systems Biology is the science of discovering, modeling, understanding and ultimately engineering at the molecular level the dynamic relationships between the biological molecules that define living organisms. Computational modeling is useful as a means to assemble and test what we know about proteins and networks. Models can help address key questions(More)