Browsing by Author "Kamath, P.R."

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Despeckling of SAR Images Using Shrinkage of Two-Dimensional Discrete Orthonormal S-Transform
(World Scientific, 2021) Kamath, P.R.; Senapati, K.; Padikkal, P.
Speckles are inherent to SAR. They hide and undermine several relevant information contained in the SAR images. In this paper, a despeckling algorithm using the shrinkage of two-dimensional discrete orthonormal S-transform (2D-DOST) coefficients in the transform domain along with shock filter is proposed. Also, an attempt has been made as a post-processing step to preserve the edges and other details while removing the speckle. The proposed strategy involves decomposing the SAR image into low and high-frequency components and processing them separately. A shock filter is used to smooth out the small variations in low-frequency components, and the high-frequency components are treated with a shrinkage of 2D-DOST coefficients. The edges, for enhancement, are detected using a ratio-based edge detection algorithm. The proposed method is tested, verified, and compared with some well-known models on C-band and X-band SAR images. A detailed experimental analysis is illustrated. © 2021 World Scientific Publishing Company.
New luminescent 2-methoxy-6-(4-methoxy-phenyl)-4-p-tolyl-nicotinonitrile: Synthesis, crystal structure, DFT and photophysical studies
(2014) Ahipa, T.N.; Kamath, P.R.; Kumar, V.; Vasudeva Adhikari, A.V.
In the current communication, we report the synthesis, spectroscopic, crystal structure, DFT and photophysical studies of a new nicotinonitrile derivative, viz. 2-methoxy-6-(4-methoxy-phenyl)-4-p-tolyl-nicotinonitrile (2) as a potential blue light emitting material. The compound 2 was synthesized in good yield via a simple route. The acquired spectral and elemental analysis data were in consistent with the chemical structure of 2. The single crystal study further confirms its three dimensional structure, molecular shape, and nature of short contacts. Its DFT calculations reveal that compound 2 possesses a non-planar structure and its theoretical IR spectral data are found to be in accordance with experimental values. In addition, its UV-visible and fluorescence spectral measurements prove that the compound exhibits good absorption and fluorescence properties. Also, it shows positive solvatochromic effect when the solvent polarity was varied from non-polar to polar. © 2014 Elsevier B.V. All rights reserved.
Short-term wind speed forecasting using S-transform with compactly supported kernel
(John Wiley and Sons Ltd, 2021) Kamath, P.R.; Senapati, K.
This paper presents a modified S-transform (ST) based on a compactly supported kernel. A version of Cheriet-Belochrani (CB) kernel is chosen for this purpose. It is shown that the proposed modified S-transform (CBST) offers better frequency resolution than the traditional ST. It is used to decompose the wind speed time series into frequency-based subseries. Further, artificial neural network (ANN) is applied to each of the subseries for an hour ahead prediction. Finally, forecast for the original wind speed series is obtained by combining the prediction result of all the subseries. Initially, increasing the number of subseries results in a decrease in prediction error. However, when the number of subseries is sufficiently large, no significant change in prediction error is observed if the number is further increased. It is also observed that, for a model based on neural-network, involving decomposition of wind speed time series, the proposed model offers low prediction error. A comparative study with the methods based on wavelet transform (WT) and empirical mode decomposition (EMD) demonstrates the effectiveness of the proposed method. For this study, we have used simulated wind speed data generated by nonhydrostatic mesoscale model and data recorded using anemometer and LiDAR instrument at different heights to evaluate the short-term forecasting results. © 2020 The Authors. Wind Energy published by John Wiley & Sons Ltd
Timeâ€“Frequencyâ€“Phase analysis for automatic detection of ocular artifact in EEG signal using S-transform
(Springer Verlag service@springer.de, 2019) Senapati, K.; Kamath, P.R.
Artifacts are unwanted components in the EEG signals which may affect the EEG signal reading, thereby not allowing the signal to be interpreted properly. One of the most common artifacts is the ocular artifact. This artifact arises due to the movement of the eye including eye blink. In most cases, detection of ocular artifacts in EEG signals is done by skilled professionals who are small in number. This paper proposes a new approach of automatic detection of ocular artifacts using the phase information present in the S-transform (ST) of EEG signal. S-transform of a signal provides absolutely referenced phase information of the signal in addition to timeâ€“frequency information. A time delay exists between the signals recorded by electrodes placed at different distances from the point of origin of the artifact. This time delay translates to phase delay in the frequency domain. The phase information of the EEG signal recorded from different electrodes placed in the frontal region is used to detect the artifacts which are generated near the region where the eye is located. Â© Springer Nature Singapore Pte Ltd 2019.
Time�Frequency�Phase analysis for automatic detection of ocular artifact in EEG signal using S-transform
(2019) Senapati, K.; Kamath, P.R.
Artifacts are unwanted components in the EEG signals which may affect the EEG signal reading, thereby not allowing the signal to be interpreted properly. One of the most common artifacts is the ocular artifact. This artifact arises due to the movement of the eye including eye blink. In most cases, detection of ocular artifacts in EEG signals is done by skilled professionals who are small in number. This paper proposes a new approach of automatic detection of ocular artifacts using the phase information present in the S-transform (ST) of EEG signal. S-transform of a signal provides absolutely referenced phase information of the signal in addition to time�frequency information. A time delay exists between the signals recorded by electrodes placed at different distances from the point of origin of the artifact. This time delay translates to phase delay in the frequency domain. The phase information of the EEG signal recorded from different electrodes placed in the frontal region is used to detect the artifacts which are generated near the region where the eye is located. � Springer Nature Singapore Pte Ltd 2019.