A near-lossless predictive compression encoding based on hexagonal sampling

In this paper, a method for lossless and near-lossless compression of large digital images is proposed. This method is based on the hexagonal sampling for predictive encoding. First, the original rectangular-based image is converted to hexagonal-based image. Then, the converted image is segmented to hexagonal sub-images with different side length. We illustrate the efficiency of the proposed approach by applying it to a series of digital images. The simulation results demonstrate that compared with the traditional predictive encoding, our lossless compression method can offer a 37.35% improvement of Peak Signal to Noise Ratio (PSNR), and a 5.5% improvement of compression ratio.