Initialization algorithm for lossless image compression with vector quantization

In this article we propose a novel algorithm for lossless image compression based on 8 × 8 px block division and vector quantization.Each block is assigned to one of k classes and encoded using linear predictor assigned to a class (calculated using the Iterative Reweighted Least Squares (IRLS) algorithm).Several methods for initializing classes based on binary division of a set are proposed.Their advantages and disadvantages are shown, and the best performing ones are selected in order to develop an original dictionary initialization algorithm, which is used in the vector quantization method adapted to the lossless image compression.The hierarchical, binary tree-based initialization method is a combination of these algorithms, in which class initialization procedure follows the pattern of a complete binary tree with k leaves.The proposed initialization method significantly reduced time required for the main vector quantization process.Proposed codec belongs to the time-asymmetric compression methods with a short decoding time and is characterized by high compression efficiency, offering on average a 7.22% lower bit average compared to JPEG-LS.