• Journal of Broadcast Engineering
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• v.9 no.3
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• pp.246-256
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• 2004

In this paper, we proposed a new lossless image compression algorithm. Lossless image compression has been used in the field that requires the accuracy and precision. Thus, application areas using medical unaging, prepress unaging, image archival systems, precious artworks to be preserved, and remotely sensed images require lossless compression. The compression ratio from lossless image compression has not been satisfactory, thus far. So, new method of lossless image compression has been investigated to get better compression efficiency. We have compared the compression results with the most typical compression methods such as CALIC and JPEG-LS. CALIC has shown the best compression-ratio among the existing lossless coding methods at the cost of the extensive complexity by three pass algorithm. On the other hand, JPEG-LS's compression-ratio is not higher than CALIC, but was adopted as an international standard of ISO because of the low complexity and fast coding process. In the proposed method, we adopted an adaptive predictor that can exploit the characteristics of individual images, and an adaptive arithmetic coding with multiple probability models. As a result, the proposed algorithm showed 5％ improvement in compression efficiency in comparison with JPEG-LS and showed comparable compression ratio with CALIC.

• Journal of Internet Computing and Services
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• v.17 no.3
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• pp.45-54
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• 2016

Medical images are an effective means to identity medical abnormalities.. Patients typically have medical images taken at different clinics during lifetime, and they often wish to have second interpretation on medical images showing substantial diseases. At present, since personal medical images are distributed to multiple clinics, there is a bit discomfort that patients directly bring their images by hands to get the second interpretation from another physician. With these two motivations, we design a cloud service for archiving medical images and interpreting medical images by physicians. We present the design and implementation of the service, and show its practical value as low-cost personal healthcare service. By using the service, patients can retrieve and review their medical images anytime and have a convenience of acquiring second opinions on their medical images at low-cost without visiting a clinic.