Quantitative Multiscale Analysis using Different Wavelets in 1D Voice Signal and 2D Image
Mutiscale analysis represents multiresolution scrutiny of a signal to improve its signal quality. Multiresolution analysis of 1D voice signal and 2D image is conducted using DCT, FFT and different wavelets such as Haar, Deubachies, Morlet, Cauchy, Shannon, Biorthogonal, Symmlet and Coiflet deploying the cascaded filter banks based decomposition and reconstruction. The outstanding quantitative analysis of the specified wavelets is done to investigate the signal quality, mean square error, entropy and peak-to-peak SNR at multiscale stage-4 for both 1D voice signal and 2D image. In addition, the 2D image compression performance is significantly found 93.00% in DB-4, 93.68% in bior-4.4, 93.18% in Sym-4 and 92.20% in Coif-2 during the multiscale analysis.
Keywords: Quantitative, Multiscale Analysis, Different Wavelets, One Dimensional Voice Signal, Two Dimensional Image.
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ABOUT THE AUTHOR
Niraj Shakhakarmi
Dr. Niraj Shakhakarmi worked as a Doctoral researcher from 2009 to 2011 in the US ARO (Army Research Office) funded Center for Battlefield Communications (CeBCom) Research, Department of Electrical and Computer Engineering, Prairie View A&M University (Texas A&M University System). He received his B.E. degree in Computer Engineering in 2005 and M.Sc. in Information and Communications Engineering in 2007. He has accomplished Ph.D in Electrical & Computer Engineering in 2011 from Prairie View A&M University, Houston, USA. His research interests are in the areas of Wavelets applications and Digital Image Processing, Secured Position Location & Tracking (PL&T), Cognitive Radio Networks, Mobile Ad hoc Networks, 4G Networks, Satellite Networks, QoS & Network Security, and Color Technology. He has published WSEAS journal, ICSST conference, Elsevier conference, and several papers are under review in IEEE and WSEAS journals and conference papers.
Niraj Shakhakarmi
Dr. Niraj Shakhakarmi worked as a Doctoral researcher from 2009 to 2011 in the US ARO (Army Research Office) funded Center for Battlefield Communications (CeBCom) Research, Department of Electrical and Computer Engineering, Prairie View A&M University (Texas A&M University System). He received his B.E. degree in Computer Engineering in 2005 and M.Sc. in Information and Communications Engineering in 2007. He has accomplished Ph.D in Electrical & Computer Engineering in 2011 from Prairie View A&M University, Houston, USA. His research interests are in the areas of Wavelets applications and Digital Image Processing, Secured Position Location & Tracking (PL&T), Cognitive Radio Networks, Mobile Ad hoc Networks, 4G Networks, Satellite Networks, QoS & Network Security, and Color Technology. He has published WSEAS journal, ICSST conference, Elsevier conference, and several papers are under review in IEEE and WSEAS journals and conference papers.
