DocumentCode :
1389371
Title :
Feature-directed spiral coding of magnetic resonance images
Author :
Nicholl, P.N. ; Millar, R.J.
Author_Institution :
Dept. of Comput. Sci., Ulster Univ., Newtownabbey, UK
Volume :
145
Issue :
2
fYear :
1998
fDate :
4/1/1998 12:00:00 AM
Firstpage :
131
Lastpage :
136
Abstract :
The authors investigate the encoding of magnetic resonance (MR) images of the human body using various lossless techniques, and presents a new form of spiral encoding. The algorithm used relies partially on the overall shape of the bounding contour of the image in achieving the compression and uses a traditional run-based technique combined with an adaptive Huffman coder to encode the complete image. Comparisons are made between the feature-directed spiral encoding and the traditional paths; the latter include the scanning pattern associated with the normal raster scanned display and the path for a display that could be used in following a linearised quadtree encoding. The new method tracks the `greater´ contour of the overall image and, once the path has been established and tuples recorded, the inner contours are automatically generated. The process is repeated for each of the inner contours with a reducing radius towards the centre. The results are given for the various techniques in terms of compression ratios. The new spiralling method achieves an approximate 5.29% saving over the traditional techniques and also gives structure to the compressed image
Keywords :
Huffman codes; adaptive codes; biomedical NMR; data compression; diagnostic radiography; edge detection; feature extraction; image coding; image texture; medical image processing; quadtrees; MRI; adaptive Huffman coder; algorithm; bounding contour shape; compressed image; compression ratios; feature-directed spiral coding; human body; inner contours; linearised quadtree encoding; lossless techniques; magnetic resonance images; raster scanned display; run-based technique; scanning pattern; texture mapping; tuples;
fLanguage :
English
Journal_Title :
Vision, Image and Signal Processing, IEE Proceedings -
Publisher :
iet
ISSN :
1350-245X
Type :
jour
DOI :
10.1049/ip-vis:19981917
Filename :
682173
Link To Document :
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