Digital medical image compression algorithm using adaptive Huffman coding and graph based quantization based on IWT SVD
Currently, the data storage medium in digital form are widely applied in various fields, including in the medical world. The excessive size of the digital medical image digital poses problems in terms of storage and the time to transmit these images through the Internet. To overcome these problems, a digital image compression can be conducted. This procedure is conducted to maintain the image quality therefore it does not affect the outcome of a medical image diagnosis. In [1] it has carried out and examined the implementation of the wavelet based image compression SVD, where the quantity process using graph coloring and for entropy encoding using Arithmetic Coding. In this paper, the data used is a medical image. Furthermore, it has been designed an image compression system based on Integer Wavelet Transform (IWT) and SVD. Graph based quantization used still refers to [1] but entropy encoding used is adaptive Huffman coding. In addition, IWT used in this system because it is reversible. Performance compression system designed to produce an average PSNR value in the range of 50 53 dB and the compression ratio ranges from 78 85%
2016 4th International Conference on Information and Communication Technology (ICoICT)