Wavelet transform in image compression



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Texas Tech University


The past few years have seen a rapid development in the areas of image compression techniques. The evolution in image compression is mainly attributed to the need of rapid and efficient techniques for the storage and transmission of data among individuals. In order to achieve maximal storage and transmission capabilities, different compression algorithms should be compared in order to find an optimal technique for medical image compression. In this research, we studied the performance of different wavelet basis fiinctions and of a Wavelet Transform (WT) image coding algorithm. We characterized the performance of the wavelet coefficients and the coding algorithm by calculating the mean square error, peak signal to noise ratio, and root mean square signal to noise ratio of the reconstmcted images. In addition, we compared the WT algorithm to the current JPEG standard. We performed comparisons on standard as well as radiographic images using the above criteria in order to judge the compression characteristics of both techniques. In addition, we show that the Adelson 15 wavelet coefficients perform better than Daubechies 4 and 12 wavelet coefficients for image compression. Furthermore, we show that JPEG and the WT algorithm had comparable performance in standard image compression, but the WT algorithm outperformed JPEG in all the above criteria and proved to be a versatile coding technique for radiographic images.