Bat optimization based vector quantization algorithm for medical image compression

Abstract

Image compression plays a significant role in medical data storage and transmission. The lossless compression algorithms are generally preferred for medical images. The variants of lossy vector quantization algorithm are also used in many cases, where the reconstructed image quality is fairly good with optimum compression ratio. Bat optimization algorithm is formulated based on the biological trait of bats to detect prey and avoid obstacles by using echolocation. In this chapter, the application of bat optimization algorithm in medical image compression is highlighted. The bat optimization algorithm is employed here for the optimum codebook design in Vector Quantization (VQ) algorithm. The performance of the BAT-VQ compression scheme was compared with the Classical VQ, Contextual Vector Quantization (CVQ) and JPEG lossless schemes for the abdomen CT images. Satisfactory results were obtained by BAT-VQ in terms of picture quality measures.