Sampling rate conversion for two-dimensional signals
This project will compute the interpolation of 2-D signals for band- limited sequence in order to reconstruct the image from a lower sampling rate to higher sampling rate. Here the Fast-Fourier Transform (FFT) has been introduced to increase the accuracy and efficiency of the interpolation process....
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sg-ntu-dr.10356-534782023-07-04T15:37:35Z Sampling rate conversion for two-dimensional signals Vangapelli Rakesh Bi Guoan School of Electrical and Electronic Engineering DRNTU::Engineering::Electrical and electronic engineering This project will compute the interpolation of 2-D signals for band- limited sequence in order to reconstruct the image from a lower sampling rate to higher sampling rate. Here the Fast-Fourier Transform (FFT) has been introduced to increase the accuracy and efficiency of the interpolation process. The frequency domain and the time domain for sampling rate conversion of two-dimensional signals will be evaluated. Implementation of these conversion techniques will be carried out based on MATLAB implementations. Problem in frequency domain interpolation for large signals (i.e., signals with larger area of support) can be solved by dividing the signal into several sub signals (i.e., signals with smaller area of support compared to that of large signal). Then the process of interpolation can be done to obtain the result of each individual signals and combining all those sub signals into a large area of support signal. Studies on performance in terms of both objective and subjective evaluations will be made. Possible methods for performance improvement will be found. Master of Science (Signal Processing) 2013-06-04T03:51:54Z 2013-06-04T03:51:54Z 2012 2012 Thesis http://hdl.handle.net/10356/53478 en 58 p. application/pdf |
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DRNTU::Engineering::Electrical and electronic engineering Vangapelli Rakesh Sampling rate conversion for two-dimensional signals |
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This project will compute the interpolation of 2-D signals for band- limited sequence in order to reconstruct the image from a lower sampling rate to higher sampling rate. Here the Fast-Fourier Transform (FFT) has been introduced to increase the accuracy and efficiency of the interpolation process. The frequency domain and the time domain for sampling rate conversion of two-dimensional signals will be evaluated. Implementation of these conversion techniques will be carried out based on MATLAB implementations. Problem in frequency domain interpolation for large signals (i.e., signals with larger area of support) can be solved by dividing the signal into several sub signals (i.e., signals with smaller area of support compared to that of large signal). Then the process of interpolation can be done to obtain the result of each individual signals and combining all those sub signals into a large area of support signal. Studies on performance in terms of both objective and subjective evaluations will be made. Possible methods for performance improvement will be found. |
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Bi Guoan |
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Bi Guoan Vangapelli Rakesh |
format |
Theses and Dissertations |
author |
Vangapelli Rakesh |
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Vangapelli Rakesh |
title |
Sampling rate conversion for two-dimensional signals |
title_short |
Sampling rate conversion for two-dimensional signals |
title_full |
Sampling rate conversion for two-dimensional signals |
title_fullStr |
Sampling rate conversion for two-dimensional signals |
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Sampling rate conversion for two-dimensional signals |
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sampling rate conversion for two-dimensional signals |
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2013 |
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http://hdl.handle.net/10356/53478 |
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1772825616851140608 |