Abstract
Wavelets are mathematical functions that catch up data into different frequency components and study each component with a resolution matched to its scale. They have advantage over traditional Fourier methods in analyzing physical situations where the signal contains discontinuities and sharp spikes. Wavelets were developed independently in the fields of mathematics, quantum physics, electrical engineering, and seismic geology. Interchanges between these fields during the last ten years have led to many new wavelet applications such as image compression, turbulence, human vision, radar, and earth quake prediction Proposed methodology provides image compression and de-noising better than existing technologies.
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