Hexagonal Image Processing develops and presents a novel framework for hexagonal image processing by taking cues from human visual system and tiling theory. This frame work is called the HIP framework and provides a solution for conversion between square sampled images and hexagonally sampled images, and processing in both the spatial and frequency domains. This framework is tested by implementing several basic image processing techniques and some novel applications are implemented such as finding points of interest and shapes using saccadic exploration. The HIP framework serves as a tool for comparing processing of images defined on a square vs hexagonal grid, to determine their relative merits and demerits. Comparisons and case studies are used in the assessment. Hexagonal sampling lattices have been considered by researchers in image processing for a long time as an efficient alternative to the conventional square sampling. This book addresses the benefits over the conventional approach.