Abstract
In recent times, the medical imaging becomes an indispensable tool in clinical practice. Due to the large volume of medical images, compression is needed to lessen the redundancies in the image and also to represent the image in shorter manner for effective transmission. In this paper, Linde–Buzo–Gray (LBG) algorithm was developed with vector quantization (VQ) for compressing the images, and it results in decent image quality. To further increase the image quality, optimization techniques [particle swarm optimization (PSO) and firefly algorithm (FA)] were used in LBG method to optimize the codebook for generating the global codebook. In the proposed work, LBG method was used to get the local codebooks and the obtained local codebooks were optimized by utilizing PSO. The optimized codebooks from PSO were again optimized by using FA that results in good quality of the image. In the experimental phase, the performance of the proposed work was compared with individual optimization techniques like PSO and FA. From the experimental study, the proposed work showed 1.2–6 dB improvement in image compression related to other existing approaches.
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More From: Journal of Ambient Intelligence and Humanized Computing
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