Color Image Coding Based on Hexagonal Discrete Cosine Transform

Traditionally, the most commonly used sampling lattice in image processing systems is the rectangular sampling lattice. However, the minimum sampling density for a hexagonal sampling lattice is 13.4% less than that for a rectangular sampling lattice when the image signals which are band limited over a circular region of the Fourier plane. Hexagonal discrete cosine transform is applied to color image compression in this paper. The original rectangular-based image is converted to hexagonal-based image first. Then, the image converted is segmented to hexagonal sub-images with different side length instead of rectangular ones. The transform coefficients obtained by HDCT are quantized and manipulated by entropy coding. The experiment results are given and show that there is higher compression ratio with our methods on the premise of ensuring the image quality.