Authors : Vidya Sharma
Page Nos : 8-13
Description :
Multi resolution techniques are deeply related to image or signal processing, biological and computer vision, scientific computing, optical data analysis. Improving quality of noisy signals or images has been an active area of research in many years. Wavelet transform can achieve good scarcity for spatially localized details, such as edges and singularities. Wavelet transform is emerged as the most effective technique for signal processing and image analysis as an alternative to Fourier analysis especially when the signals are random, comprised of fluctuations of different scales and where the very short and very long waves are present in the same signal.
In the present work a strong relationship between Wavelet transform and fractional Fourier transform is presented. Analytical behavior of extended Wavelet transform is exploited which can be viewed as extension of fractional Fourier transform. This interpretation of Wavelet transform in terms of fractional Fourier transform is then used in the far reaching applications especially in the field of signal processing and in particular, in the field of long range optical fiber transmission, which has been an active area of research ever since the introduction of multi resolution techniques in the fractal representation of modulated signals. Experimental results have shown that the wavelet based models have better performance over the other transform techniques ever applied for signal processing.
