Analysis of multi scale features of compressed medical images

Image files contain considerable amount of redundant and irrelevant data and image compression algorithms can be used to overcome this. In this work, Wavelet Transform based compression algorithm is employed. Haar and daubechies wavelets are utilized in this proposed work for the decomposition of the medical image and the decomposed images are encoded using the schemes such as Embedded Zero wavelet, (EZW), Set Partitioning In Hierarchical Trees (SPIHT), Spatial orientation Tree Wavelet (STW), Wavelet Difference Reduction (WDR) and Adaptively Scanned Wavelet Difference Reduction (ASWDR). The computer tomography image is undergone the various developed compression techniques. The proposed compression schemes are evaluated in terms of PSNR, Compression ratio, Means square error and bits per pixel. The optimum compression algorithm is also found based on the results. The results are an indicator to the promising application of this for medical image compression schemes. This paper provides the approach and analysis methodologies and the results obtained.