Edge Directed Prediction for Lossless Compression of Natural Images

This paper sheds light on the recent least-square (LS)-based adaptive prediction schemes for lossless compression of natural images. Our analysis shows that the superiority of the LS-based adaptation is due to its edge-directed property, which enables the predictor to adapt reasonably well from smooth regions to edge areas. Recognizing that LS-based adaptation improves the prediction mainly around the edge areas, we propose a novel approach to reduce its computational complexity with negligible performance sacrifice. The lossless image coder built upon the new prediction scheme has achieved noticeably better performance than the state-of-the-art coder CALIC with moderately increased computational complexity.

• Type: Conference
• Year: 1999
• Where: ICIP
• Authors: Xin Li, Michael T. Orchard
• Keywords: Adaptive Prediction Schemes, ICIP 1999, Image Processing, LS-based Adaptation, Prediction Scheme