A Hybrid Image Compression Technique using Quadtree Decomposition and Parametric Line Fitting for Synthetic Images

This paper presents a new hybrid scheme for image data compression using quadtree decomposition and parametric line fitting. In the first phase of encoding, the input image is partitioned into quadrants using quadtree decomposition. To prevent from very small quadrants, a constraint of minimal block size is imposed during quadtree decomposition. Homogeneous quadrants are separated from non-homogeneous quadrants. In the second phase of encoding, the non-homogeneous quadrants are scanned row-wise. Luminance variation of each scanned row is fitted using parametric line at specified level of tolerance. The output data is entropy coded. Experimental results show that the proposed scheme performs better than well-known lossless image compression techniques for several types of synthetic images, e.g., clip-art, cartoon, animation, scientific plot, medical image etc. keywords: image, compression, quadtree, parametric line, fitting.