Adaptive Lifting Based Image Compression Scheme Using Artificial Bee Colony Algorithm

The increment in the sizes of the images by the technological advances accompanies high demand for large capacities, high performance devices, high bandwidths etc. Therefore, image compression techniques are essential to reduce storage, computational or transmittal costs. Wavelet transform is one of the compression techniques especially used for images and multimedia files. This paper, proposes a framework for constructing adaptive update for lifting scheme. Artificial bee colony algorithm is used to find different update coefficient by local search, at last optimally choose the best update coefficient to get best quality of compressed image. In the update step we modifying the center pixels with the co-efficient in 8 – different direction with a considerable window size by using local search, we obtain a best directional window with a considerable size using artificial bee colony algorithm to obtain the best reconstructed image, which can be considered as an optimization task. Artificial Bee Colony algorithm which is a recent and successful optimization tool is used to determine the directional window size to produce the best compressed image in terms of both compression ratio and quality. The proposed work gives better PSNR when compared to existing methods. So, the transmission cost to transmit the encoded data and memory space to store the encoded data can be reduced with help of adaptive update lifting scheme with artificial bee colony algorithm.