Abstract
The fundamental goal of image data compression is to set an optimal compression ratio while maintaining an acceptable reproduction quality. This study describes the principles of design of image compression system that automatically sets an optimal compression ratio for particular image content by identifying the image compression method while maintaining a tolerable reproduction quality. The proposed image compression system employs subjective and objective criteria for an assessment of the quality of the image compression system. The supervised artificial neural network is used to identify a compression method among different compression techniques by using subjective criterion. An objective criterion is used to determine an optimal compression ratio, which is calculated by using linear regression analysis that establishes analytical expression between a compression ratio, a property of an image and a reconstructed quality of an image. It was proved that the system is an effective tool for medical image compression applications.
Published Version
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