Title :
Statistical distributions of DCT coefficients and their application to an interframe compression algorithm for 3-D medical images
Author :
Lee, Heesub ; Kim, Yongmin ; Rowberg, Alan H. ; Riskin, Eve A.
Author_Institution :
Washington Univ., Seattle, WA, USA
fDate :
9/1/1993 12:00:00 AM
Abstract :
Displacement estimated interframe (DEI) coding, a coding scheme for 3-D medical image data sets such as X-ray computed tomography (CT) or magnetic resonance (MR) images, is presented. To take advantage of the correlation between contiguous slices, a displacement-compensated difference image based on the previous image is encoded. The best fitting distribution functions for the discrete cosine transform (DCT) coefficients obtained from displacement compensated difference images are determined and used in allocating bits and optimizing quantizers for the coefficients. The DEI scheme is compared with 2-D block discrete cosine transform (DCT) as well as a full-frame DCT using the bit allocation technique of S. Lo and H.K. Huang (1985). For X-ray CT head images, the present bit allocation and quantizer design, using an appropriate distribution model, resulted in a 13-dB improvement in the SNR compared to the full-frame DCT using the bit allocation technique. For an image set with 5-mm slice thickness, the DEI method gave about 5% improvement in the compression ratio on average and less blockiness at the same distortion. The performance gain increases to about 10% when the slice thickness decreases to 3 mm
Keywords :
biomedical NMR; computerised tomography; data compression; medical image processing; 3 mm; 5 mm; X-ray computed tomography; best fitting distribution functions; bit allocation; compression ratio; displacement-compensated difference image; distribution model; head images; interframe compression algorithm; magnetic resonance images; quantizer design; slice thickness; statistical distribution; Biomedical imaging; Bit rate; Computed tomography; Discrete cosine transforms; Distribution functions; Head; Image coding; Magnetic resonance; Statistical distributions; X-ray imaging;
Journal_Title :
Medical Imaging, IEEE Transactions on