In the recent growth of data intensive and multimedia based applications, efficient image compression solutions are becoming critical. The main objective of Image Compression is to reduce redundancy of the data and improve the efficiency. The main techniques used are Fourier Analysis, Discrete Cosine Transform vector quantization method, sub-band coding method. The drawbacks in the above methods are, they cannot be used for real time systems. In order to overcome these problems, the Wavelet Transform method has been introduced. Wavelet Analysis is highly capable of revealing aspects of data like trends, breakdown points, discontinuities in higher derivates and self similarity and can often compress or diagnose a signal without appreciable degradation. Here, we implement a lossy image compression technique using Matlab Wavelet Toolbox and Matlab Functions where the wavelet transform of the signal is performed, then calculated a threshold based on the compression ratio acquired by the user.
CITATION STYLE
G.Shruthi, G. S. (2013). Image Reconstruction Using Discrete Wavelet Transform. IOSR Journal of VLSI and Signal Processing, 2(4), 14–20. https://doi.org/10.9790/4200-0241420
Mendeley helps you to discover research relevant for your work.