Wavelet Transforms And Image Approximation Based Image Compression System

The purpose of this work is to design an efficient image compression system using wavelet transforms and image approximation by modifying the wavelet coefficient. The efficiency of the system will be tested using a test image and determining the Mean Square Error (MSE). 2D-daubechies wavelet transformation with global threshold for wavelet coefficients and numerical presentation utilizing Matlab programming are the techniques used. The Discrete Wavelet Transform (DWT) has a basic principle of splitting signals into two parts namely; the high frequencies and low frequencies. For a number of repetitions, the low frequency section is further divided into high and low frequency parts, which are generally chosen by the application. The performance of an image compression system is commonly measured by calculating the MSE and the Peak Signal to Noise Ratio (PSNR).

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