A new efficient predictor blending lossless image coder

Abstract

In the paper a highly efficient algorithm for lossless image coding is described. The algorithm is a predictor blending one, a sample estimate is computed as a weighted sum of estimates given by subpredictors, here 27 ones, hence the name Blend-27. Data compaction performance of Blend-27 is compared to that of numerous other lossless image coding algorithms, including the best currently existing ones. The compared methods are ”classical” ones, as well as those based on Artificial Neural Networks. Performance of Blend-27 as a near-lossless coder is also evaluated. Its computational complexity is lower than that of majority of its direct competitors. The new algorithm appears to be currently the most efficient technique for lossless coding of natural images.