Novel Quadtree Image Coding Technique Using Edge-Oriented Classification

摘要

A new image compression approach is proposed in which variable block size technique is adopted, using quadtree decomposition, for coding images at low bit rates. In the proposed approach, low-activity regions, which usually occupy large areas in an image are coded with a larger block size and the block mean is used to represent each pixel in the block. A novel classification scheme, which operates based on the distribution of the block residuals is employed to determine whether the processed block is a low-detail or a high-detail block. To preserve edge integrity, a new edge-based coding technique is used to code high-activity regions. In this method, the orientation of edge pattern within a high-activity block will be computed as an aid to the classification. A novel edge-oriented classifier, operating based on the histogram analysis of the pixels' orientations, is also proposed to for edge classification. Each edge block is represented by a set of parameters associated with the pattern appearing inside the block. The use of these parameters at the receiver reduces the cost of reconstruction significantly and exploits the efficiency of the proposed technique. Experiments have been conducted to compare with variance-based quadtree technique, vector quantization-based variable size algorithms, as well as the standard JPEG. Results show higher PSNR at competitive reconstruction quality.