Wavelet-based medical image compression
Future Generation Computer Systems - Special issue on ITIS—an international telemedical information society
Matrix Cubic Splines for Progressive 3D Imaging
Journal of Mathematical Imaging and Vision
Wavelets for Computer Graphics: A Primer, Part 1
IEEE Computer Graphics and Applications
Matrix newton interpolation and progressive 3D imaging: PC-based computation
Mathematical and Computer Modelling: An International Journal
Progressive transmission of images: PC-based computations, using orthogonal matrix polynomials
Mathematical and Computer Modelling: An International Journal
Computer Methods and Programs in Biomedicine
SVD lossy adaptive encoding of 3D digital images for ROI progressive transmission
Image and Vision Computing
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Two progressive transmission procedures that are adaptive are developed, for any 3-D image which is composed from n, disjoint regions of any type. Each of the two is responsive to both the particular reconstruction process employed at the recipient node and the detail within the image. If some of the regions have already been transmitted, a next from among the remainder can be selected through an individually-best remaining region (IBRR) or a globally-best remaining region (GBRR) strategy. For each, its ordering template need to be determined only once, a priori. GBRR's sequence information requires considerably more CPU resources to obtain, but the resulting progressive technique can be more effective, as is illustrated using a test set consisting of 93 CT slices (resolution 256 x 256) of a human head. An algorithm is developed for automatically decomposing any 3-D images into regions that are not of the ''parallel plane slicing'' variety. Then, Experiment 2 illustrates effectiveness of IBRR (and hence, also GBRR) sequencing for a CT phantom, when this non-parallel plane decomposition replaces a parallel plane decomposition of it. Both IBRR and GBRR generalize to the setting of 4-D data sets generated from dynamic MR imaging, for example.