Abstract
Medicine is benefited in large amount with the utilization of imaging. Magnetic Resonance Imaging (MRI) is an important imaging modality that is used for better diagnosis. Since the number of images generated by MRI is in large number per patient, the requirement for storage space and transmission bandwidth will be larger. In the area of image processing, image compression finds an important application that reduces storage space and transmission bandwidth. One way to compress the image is by using transform based techniques. In this work, we have used DWT (Discrete Wavelet Transform) with multiple wavelets at different levels to transform the MRI images. In the first few levels CDF (Cohen–Daubechies–Feauveau) 9/7 wavelet is used for transformation and Haar wavelet is used for remaining levels. After transformation SPIHT (Set Partitioning In Hierarchical Trees) algorithm is used for compression of the images. We have observed better compression in terms of MSE (Mean squared Error) and PSNR (Peak Signal to Noise Ratio) with the proposed method in comparison with the single wavelet transformation.
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