ADAPTIVE IMAGE CODING FOR DATA COMPRESSION OF X-RAY PICTURES
| dc.contributor.advisor | Takaya, K. | |
| dc.creator | Patel, Rameshchandra Manibhai | |
| dc.date.accessioned | 2019-01-21T21:22:00Z | |
| dc.date.available | 2019-01-21T21:22:00Z | |
| dc.date.issued | 1979-04 | |
| dc.date.submitted | April 1979 | en_US |
| dc.description.abstract | Digital transmission, storage, and retrieval of medical X-ray pictures is a feasible concept using today's technology. The large amounts of data can be compressed by image coding techniques. It is necessary, however, to adapt the corresponding coding procedures to suit X-ray picture statistics. This thesis assesses two well known information preserving coding schemes with respect to the statistical examination of X-ray pictures. The first is a modified Shannon-Fano coding scheme. Thes scheme is made adaptive by using the local entropy information of the picture. This scheme is more suitable for encoding high entropy regions of the picture. The second method is based on Golomb's runlength coding algorithm, which is used for encoding bitplanes in grey level picture. By measuring the run-length statistics of each scan line of data in the X-ray picture, this scheme is made adaptive. This scheme gives better performance for encoding low entropy regions of the picture. Finally, these two adaptive schemes are combined to form a single adaptive scheme to suit overall X-ray picture statistics. It was found that by combining these two schemes, higher data compression can be achieved than by either individual scheme. | en_US |
| dc.identifier.uri | http://hdl.handle.net/10388/11762 | |
| dc.title | ADAPTIVE IMAGE CODING FOR DATA COMPRESSION OF X-RAY PICTURES | en_US |
| dc.type.genre | Thesis | en_US |
| thesis.degree.department | Electrical and Computer Engineering | en_US |
| thesis.degree.discipline | Electrical Engineering | en_US |
| thesis.degree.grantor | University of Saskatchewan | en_US |
| thesis.degree.level | Masters | en_US |
| thesis.degree.name | Master of Science (M.Sc.) | en_US |
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