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Image compression in matlab using modified haar wavelet transform

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Haar transform is one of the simplest and basic transformation from the
multi-resolution spectrum. The attracting features obtained from Haar
transform make it a potential candidate in modern applications, such as
signal and image compression. The Haar wavelet transform provides mean
values that compress the image so that it takes up much less storage
space, and therefore transmits faster electronically and in progressive
levels of detail. The main objective of this work is to modify the weighting
factor in or der to study their effects on image compression. This paper
tries to implement different scale of weighting factor and study their
performance on the overall system of compression. Scale of weighting
factor is used in order to prevent the pixel value from exceeding their limits.
Different values of weighting factor are applied, these values are spans into
two range to evaluate the implemented system. These values are
implemented for various levels of 2D-DWT then we measure the
performance via mean square error (MSE) and peak signal to noise ration
(PSNR) in each step. The implemented system is simulated for wide range
of weighting factors. The obtained results indicated that a good results can
be achieved between a=1.6 to a=5.0.

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