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A new scheme for a still image encoder using vector quantization (VQ) is proposed. The new method classifies the block into a suitable class and predicts both the classification type and the index information. To achieve better performance, the encoder decomposes images into smooth and edge areas by a simple method. Then, it encodes the two kinds of region using different algorithms to promote the compression efficiency. Mean-removed VQ (MRVQ) with block sizes 8×8and 16×16pixels compress the smooth areas at high compression ratios. A predictive classification VQ (CVQ) with 32 classes is applied to the edge areas to reduce the bit rate further. The proposed prediction method achieves an accuracy ratio of about 50 when applied to the prediction of 32 edge classes. Simulation demonstrates its efficiency in terms of bit rate reduction and quality preservation. When the proposed encoding scheme is applied to compress the “Lena” image, it achieves the bit rate of 0.219 bpp with the peak SNR (PSNR) of 30.59 dB. © 2000 Society of Photo-Optical Instrumentation Engineers.

Conventional medical image compression systems employ full-frame processing to avoid the blocking effect, which may lead to the incorrect diagnosis. But full-frame processing is time consuming and, worse, results in the blurring of sharp regions when the compression ratio is high. A new medical image compression technique based on 2×2discrete cosine transform (DCT) is proposed. The 2×2DCT has the ability to retain the detail characteristics of an image. Furthermore, it has the benefit of low computational complexity. By means of a simple transformation to gather the spectrum data with the same frequency domain and an information dominance strategy, the new compression technique promotes efficient coding when applied in the practical data management systems. The simulations are carried out on different types of medical images to evaluate the performance of the proposed scheme. The results verify the efficiency in terms of compression ratio, reconstruction quality, and processing time. © 1998 Society of Photo-Optical Instrumentation Engineers..