The Joint Photographers Expert Group (JPEG) developed an image compression tool, which is one of the most widely used products for image compression. One of the factors that influence the performance of JPEG compression is the quantization table. Bit rate and the decoded quality are both determined by the quantization table simultaneously. Therefore, the designed quantization table has fatal influences to whole compression performance. The goal of this paper is to seek sets of better quantization parameters to raise the compression performance that means it can achieve lower bit while preserving higher decoded quality. In our study, we employed Genetic Algorithm (GA) to find better compression parameters for medical images. Our goal is to find quantization tables that contribute to better compression efficiency in terms of bit rate and decoded quality. Simulations were carried out for different kinds of medical images, such as sonogram, angiogram, X-ray, etc. Resulting experimental data demonstrate the GA-based seeking procedures can generate better performance than the JPEG does.
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