publications: - title: "Target Identification using Harmonic Wavelet based ISAR Imaging" author: - name: "B. K. ShreyamshaKumar" link: "http://sites.google.com/site/shreyamsha" - name: " B. Prabhakar" link: "https://researchr.org/alias/b.-prabhakar" - name: " K. Suryanarayana" link: "https://researchr.org/alias/k.-suryanarayana" - name: " V. Thilagavathi" link: "https://researchr.org/alias/v.-thilagavathi" - name: " Dr. R. Rajagopal" link: "https://researchr.org/alias/dr.-r.-rajagopal" year: "2006" doi: "http://dx.doi.org/10.1155/ASP/2006/86053" abstract: "A new approach has been proposed to reduce the computations involved in the ISAR imaging, which uses Harmonic Wavelet (HW) based Time-Frequency Representation (TFR). Since the HW based TFR falls into a category of non-parametric Time-Frequency (T-F) analysis tool, it is computationally efficient compared to parametric T-F analysis tools such as Adaptive Joint Time-Frequency Transform (AJTFT), Adaptive Wavelet Transform (AWT) and Evolutionary AWT (EAWT). Further, the performance of the proposed method of ISAR imaging is compared with the ISAR imaging by other non-parametric T-F analysis tools such as Short Time Fourier Transform (STFT) and Choi-Williams Distribution (CWD). In the ISAR imaging, the use of HW based TFR provides similar/better results with significant (92%) computational advantage compared to that obtained by CWD. The ISAR images thus obtained are identified using a Neural Network based classification scheme with feature set invariant to translation, rotation and scaling." links: doi: "http://dx.doi.org/10.1155/ASP/2006/86053" tags: - "Inverse Synthetic Aperture Radar" - " Harmonic Wavelet" - "rule-based" - "translation" - " Cross-Range Resolution" - "classification" - " Wigner-Ville Distribution" - "analysis" - " Range Resolution" - " Feature set" - " Artificial Neural Networks" - " Time-Frequency Representation" - "systematic-approach" - " Choi-Williams Distribution" researchr: "https://researchr.org/publication/shreyamsha2006" cites: 0 citedby: 0 kind: "article" key: "shreyamsha2006" - title: "Target Identification Using Harmonic Wavelet Based ISAR Imaging" author: - name: "B. K. ShreyamshaKumar" link: "http://sites.google.com/site/shreyamsha" - name: " B. Prabhakar" link: "https://researchr.org/alias/b.-prabhakar" - name: " K. Suryanarayana" link: "https://researchr.org/alias/k.-suryanarayana" - name: " V. Thilagavathi" link: "https://researchr.org/alias/v.-thilagavathi" - name: "R. Rajagopal" link: "https://researchr.org/alias/r.-rajagopal" year: "2006" doi: "http://dx.doi.org/10.1155/ASP/2006/86053" abstract: "A new approach has been proposed to reduce the computations involved in the ISAR imaging, which uses harmonic wavelet-(HW) based time-frequency representation (TFR). Since the HW-based TFR falls into a category of nonparametric time-frequency (T-F) analysis tool, it is computationally efficient compared to parametric T-F analysis tools such as adaptive joint time-frequency transform (AJTFT), adaptive wavelet transform (AWT), and evolutionary AWT (EAWT). Further, the performance of the proposed method of ISAR imaging is compared with the ISAR imaging by other nonparametric T-F analysis tools such as short-time Fourier transform (STFT) and Choi-Williams distribution (CWD). In the ISAR imaging, the use of HW-based TFR provides similar/better results with significant (92%) computational advantage compared to that obtained by CWD. The ISAR images thus obtained are identified using a neural network-based classification scheme with feature set invariant to translation, rotation, and scaling." links: doi: "http://dx.doi.org/10.1155/ASP/2006/86053" dblp: "http://dblp.uni-trier.de/rec/bibtex/journals/ejasp/KumarPSTR06" tags: - "rule-based" - "translation" - "classification" - "analysis" - "systematic-approach" researchr: "https://researchr.org/publication/KumarPSTR06" cites: 0 citedby: 0 journal: "EURASIP J. Adv. Sig. Proc." volume: "2006" kind: "article" key: "KumarPSTR06" - title: "JPEG image encryption using fuzzy PN sequences" author: - name: "B. K. ShreyamshaKumar" link: "http://sites.google.com/site/shreyamsha" - name: " Chidamber R. Patil" link: "https://researchr.org/alias/chidamber-r.-patil" year: "2010" doi: "http://dx.doi.org/10.1007/s11760-009-0131-6" links: doi: "http://dx.doi.org/10.1007/s11760-009-0131-6" dblp: "http://dblp.uni-trier.de/rec/bibtex/journals/sivp/ShreyamshaKumarP10" researchr: "https://researchr.org/publication/ShreyamshaKumarP10" cites: 0 citedby: 0 journal: "Signal, Image and Video Processing" volume: "4" number: "4" pages: "419-427" kind: "article" key: "ShreyamshaKumarP10" - title: "Harmonic Wavelet Based ISAR Imaging For Target Identification" author: - name: "B. K. ShreyamshaKumar" link: "http://sites.google.com/site/shreyamsha" - name: " B. Prabhakar" link: "https://researchr.org/alias/b.-prabhakar" - name: " K. Suryanarayana" link: "https://researchr.org/alias/k.-suryanarayana" - name: " V. Thilagavathi" link: "https://researchr.org/alias/v.-thilagavathi" year: "2005" doi: "http://www.docstoc.com/docs/5063057/Harmonic-Wavelet-based-ISAR-Imaging-for-Target-Identification" abstract: "Target identification using Inverse Synthetic Aperture Radar (ISAR) imaging is an important tool required with the current day high-resolution radars for threat assessment and evaluation. Identification of target using the ISAR images is gaining popularity because of its importance in decision-making. The ISAR image represents the target’s reflectivity measured at discrete frequencies in the RF domain. It uses the Doppler information to obtain the cross range resolution, and the range resolution is directly related to the bandwidth of the transmitted signal. In order to capture the target information effectively, the Wigner-Ville Distribution (WVD) based ISAR imaging was proposed. But this involves high computational complexity and hence difficult to realize for practical applications. In order to reduce these computations and make it feasible for practical scenarios, the Harmonic Wavelet (HW) based ISAR imaging is proposed and the resulting images are used for target identification. The performance of the proposed scheme is compared with the Filtered Wigner-Ville Distribution (FWVD), standard STFT and FFT techniques, and found to provide better ISAR images with 92% reduction in computations. A Neural Network based Automatic Target Identification (ATI) scheme invariant to translation, rotation and scale is used for target classification." links: doi: "http://www.docstoc.com/docs/5063057/Harmonic-Wavelet-based-ISAR-Imaging-for-Target-Identification" tags: - "Inverse Synthetic Aperture Radar" - " Artificial Neural Networks." - " Harmonic Wavelet" - "rule-based" - "translation" - " Cross-Range Resolution" - "classification" - " Wigner-Ville Distribution" - " Range Resolution" - " Feature set" - " Time-Frequency Representation" researchr: "https://researchr.org/publication/HWT-based-ISAR-Imaging" cites: 0 citedby: 0 kind: "inproceedings" key: "HWT-based-ISAR-Imaging" - title: "Harmonic Wavelet Transform Signal Decomposition and Modified Group Delay for Improved Wigner-Ville Distribution" author: - name: "S. V. Narasimhan" link: "https://researchr.org/alias/s.-v.-narasimhan" - name: "B. K. ShreyamshaKumar" link: "http://sites.google.com/site/shreyamsha" year: "2004" doi: "http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1458417" abstract: "A new approach for the Wigner-Ville Distribution (WVD) based on signal decomposition by harmonic wavelet transform (SDHWT) and the modified magnitude group delay function (MMGD) has been proposed. The SDHWT directly provides subband signals and the WVD of these components are concatenated to get the overall WVD without using antialias and image rejection filtering. The SDHWT and the MMGD remove the existence of crossterms (CT) and the ripple effect due to truncation of the WVD kernel without applying any window, respectively. Since there is no time and frequency smoothing, the proposed method has a better performance in terms of both time and frequency resolution and desirable properties of a time-frequency representation (TFR) than the Pseudo WVD (PWVD). Further, it has a relatively better noise immunity compared to that of PWVD. In the WVD, for signal decomposition, the use of SDHWT, compared to that of a filter bank, provides almost similar results but has a significant (72%) computational advantage. " links: doi: "http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1458417" tags: - "rule-based" - " Harmonic Wavelet Transform" - " Wigner-Ville Distribution" - "Modified Magnitude Group Delay" - " Time-Frequency Representation" - "systematic-approach" researchr: "https://researchr.org/publication/shreyamsha-2004-1" cites: 0 citedby: 1 booktitle: "International Conference on Signal Processing and Communications (SPCOM)" kind: "inproceedings" key: "shreyamsha-2004-1" - title: "JPEG Image Encryption using Fuzzy PN Sequences" author: - name: "B. K. ShreyamshaKumar" link: "http://sites.google.com/site/shreyamsha" - name: "Chidamber R. Patil" link: "http://bel-india.com" year: "2009" doi: "http://dx.doi.org/10.1007/s11760-009-0131-6" abstract: "The recent explosion in multimedia and networking application places a great demand on efficient transmission of images at low bit rate with high security. Mixing several existing standard encryption techniques with image encoding tends to change the compression ratio greatly. In this paper, a novel image encryption algorithm is embedded as a part of JPEG image encoding scheme tomeet threemajor necessities: (1) to provide temporal security against casual observer, (2) to preserve the compression ratio, (3) remain compliant with the JPEG file format. In the proposed algorithm, the modified DCT blocks are confused by a fuzzy PN sequence. In addition to that, the DCT coefficients of each modified DCT block are converted to unique uncorrelated symbols, which are confused by another fuzzy PN sequence. Finally, the variable length encoded bits are encrypted by chaotic stream cipher. An amalgamation of all the three techniques with random combination of seeds will provide the required security against the casual listener/observer where the security needed is only in-terms of few hours." links: doi: "http://dx.doi.org/10.1007/s11760-009-0131-6" tags: - "Encryption" - " Decryption" - " Difference of quantized DC coefficient" - " Scrambling" - "security" - " Fuzzy PN sequence" - " Fuzzy random index generator" - "multimedia" researchr: "https://researchr.org/publication/Shreyamsha" cites: 0 citedby: 0 kind: "article" key: "Shreyamsha" - title: "Improved Wigner-Ville distribution performance based on DCT/DFT harmonic wavelet transform and modified magnitude group delay" author: - name: "S. V. Narasimhan" link: "https://researchr.org/alias/s.-v.-narasimhan" - name: "A. R. Haripriya" link: "https://researchr.org/alias/a.-r.-haripriya" - name: "B. K. ShreyamshaKumar" link: "http://sites.google.com/site/shreyamsha" year: "2008" doi: "http://dx.doi.org/10.1016/j.sigpro.2007.06.013" abstract: "A new Wigner–Ville distribution (WVD) estimation is proposed. This improved and efficient WVD is based on signal decomposition (SD) by DCT or DFT harmonic wavelet transform (DCTHWT or DFTHWT) and the modified magnitude group delay (MMGD). The MMGD processing can be either in fullband or subband. The SD by DCTHWT provides better quality low leakage decimated subband components. The concatenation of WVDs of the subbands results in an overall WVD, significantly free from crossterms and Gibbs ripple. As no smoothing window is used for the instantaneous autocorrelation (IACR), MMGD removes or reduces the Gibbs ripple preserving the frequency resolution achieved by the DCT/DFT HWT. The SD by DCTHWT compared to that of DFTHWT, has improved frequency resolution and detectability. These are due to the symmetrical data extension and the consequential low leakage (bias and variance). As the zeros due to the associated white noise are removed by the MMGD effectively in subband domain than in fullband, the proposed WVD based on subband has a better noise immunity. Compared to fullband WVD, the subband WVD is computationally efficient and achieves a significantly better: frequency resolution, detectability of low-level signal in the presence of high-level one and variance. The SD-based methods, however cannot bring out the frequency transition path from band to band clearly, as there will be gap in the contour plot at the transition. For the proposed methods, the heart rate variability (HRV) real data is also considered as an example." links: doi: "http://dx.doi.org/10.1016/j.sigpro.2007.06.013" tags: - " DCT harmonic wavelet transform" - "rule-based" - " DFT harmonic wavelet transform" - " Modified magnitude group delay function" - " Fullband and subband processing" - "data-flow" - "Wigner–Ville distribution" - " Heart rate variability (HRV) data" - " Signal decomposition" researchr: "https://researchr.org/publication/NarasimhanHK08" cites: 17 citedby: 0 journal: "Signal Processing" volume: "88" number: "1" pages: "1-18" kind: "article" key: "NarasimhanHK08"