Performance of wavelet based image compression on medical images for cloud computing

Healthcare researchers are moving towards their efforts to the cloud platform in order to process, store, exchange and use a large amount of medical image data which are generated and acquired through various advance medical modalities. One of the challenges that arises in hospitals and medical organizations is the difficulty of transmitting such a large volume of medical images with relatively limited bandwidth. Image compression techniques have been incorporated in order to reduce the bandwidth requirement and economically transfer of medical images for primary diagnosis. The algorithm what is discussed in this paper has been implemented using the wavelet toolbox of MATLAB. Multilevel decomposition of the original image is applied using discrete wavelet transform and then image is quantified based on hard thresholding and finally Huffman technique is applied for coding. The main concern of this study is to identify the right or most appropriate wavelets for compressing medical images. To investigate this, different wavelets were used for a selected set of medical images. The results of this study are presented in this paper. The simulation results show that the algorithm gives the better performance of image reconstruction and that the proposed algorithm can also be a good option for the image storage and retrieval on the cloud platform economically and efficiently.