Image compression using discrete cosine transform and wavelet transform and performance comparison

Abstract

Image compression deals with reducing the size of image which is performed with the help of transforms. In this project we have taken the Input image and applied wavelet techniques for image compression and have compared the result with the popular DCT image compression. WT provided better result as far as properties like RMS error, image intensity and execution time is concerned. Now a days wavelet theory based technique has emerged in different
signal and image processing application including speech, image processing and computer vision. In particular Wavelet Transform is of interest for the analysis of non-stationary signals. In the WT at high frequencies short windows and at low frequencies long windows are used. Since discrete wavelet is essentially sub band–coding system, sub band coders have been quit successful in speech and image compression. It is clear that DWT has potential application in compression problem.