Embedded medical image compression using DCT based subband decomposition and modified SPIHT data organization

In the paper, an 8×8 DCT approach is adopted to perform subband decomposition, followed by modified SPIHT data organization and entropy coding. The translation function has the ability to retain the detail characteristics of an image. By means of a simple transformation to gather the DCT spectrum data with the same frequency domain, the translation function exploits all the characteristics of all individual blocks to a global framework. In this scheme, insignificant DCT coefficients that correspond to the same spatial location in the high-frequency subbands can be used to reduce the redundancy by a combined function proposed in associated with the modified SPIHT. Simulation results showed that the embedded DCT-CSPIHT image compression reduced the computational complexity to only a quarter of the wavelet based subband decomposition and improved the quality of the reconstructed medical image in terms of both the peak PSNR and the perceptual results over JPEG2000 and the original SPIHT at the same bit rate.