An optimised clustering algorithm with dual tree DS for lossless image compression

Abstract

The emerging utilisation of web and other electronic applications have expedited much consideration on image compression systems to spare storage room and diminish transmission time by compressing the size of an image by discarding the repetitive data sequences. Most of the techniques are based on lossy compression techniques where the compression ratio would be low. The proposed system based on lossless compression technique achieves best compression ratio, good image quality and less PSNR value by extracting the best features of an image, which is to be compressed and encoded by incorporating firefly algorithm with k means algorithm there by avoids local optima problem. To make the eminent compression of best derived features, quad tree decomposition and Huffman encoding technique are combined, which provide high compression ratio by fetching correct probabilities of occurrence of pixel intensity. This proposed technique is actualised in MATLAB and in this manner the trial results demonstrated the effectiveness of the proposed image compression technique regarding high compression ratio, low noise ratio, and reduced compression and decompression time when compared with existing techniques.