Application of Krill Herd Algorithm to Improved Quasi Lossless Fractal Medical Image Compression
Rage in magnetic resonance imaging technology is growing right in the direction of accessing digital images straight. Nowadays, numerous process generates images directly in digital form for instance X-ray, ECG, EEG, etc. Storage as well as transmission plays a major role in digital imaging. To overcome the difficulties owing to the increasing size of image files, there is a need for proficient image compression methods for adequate storage and transmission of medical images. To compress medical images, improved quasi lossless fractal image compression, a sort of fractal image compression technique is used. Improved quasi lossless fractal image compression improves speed of encoding by reducing the search space. This paper utilizes the Krill Herd optimization algorithm which is applied to improved quasi lossless fractal image compression to further speed up the encoder and to preserve the medical image quality. This work represents the theoretical and practical implementation of the krill herd algorithm. It is also compared to other optimization algorithms for various medical images have also been reported here.