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A novel adaptive image compression technique using Classified Vector Quantiser and Discrete Cosine Transform is presented for the efficient representation of still images. The proposed method is called Adaptive Hybrid Classified Vector Quantisation. It involves a simple, but efficient, classifier based gradient method in the spatial domain without using any(More)
An efficient adaptive lossy image compression technique using classified vector quantiser and singular value decomposition for compression of medical magnetic resonance – brain images is presented. The proposed method is called adaptive hybrid classified vector quantisation. A simple but efficient classifier based gradient method without employing any(More)
— In the present paper, Mean Shift Algorithm and active contour to detect objects for CT Angiography Image Segmentation is proposed.Based on the results we believe that this method of boundary detection together with the mean-shift can achieve fast and robust tracking of the CT Angiography Image Segmentation in noisy environment. The proposed scheme has(More)
A novel image compression technique using classified vector quantiser and singular value decomposition is presented for the efficient representation of still images. The proposed method is called hybrid classified vector quantisation. It involves a simple, but efficient, classifier based gradient method in the spatial domain which employs only one threshold(More)
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