Image mosaicing is the act of combining two or more images and is used in many applications in computer vision, image processing, and computer graphics. It aims to combine images such that no obstructive boundaries exist around overlapped regions and to create a mosaic image that exhibits as little distortion as possible from the original images. In the proposed technique, the to-be-combined images are first projected into wavelet subspaces. The images projected into the same wavelet space are then blended. Our blending function is derived from an energy minimization model which balances the smoothness around the overlapped region and the fidelity of the blended image to the original images. Experiment results and subjective comparison with other methods are given.

Wen-Liang Hwang received the Ph.D. degree from the Computer Science Department, New York University, New York, in 1993. He was a Postdoctoral Researcher in the Mathematics Department, University of California, Irvine, in 1994. He became a member of the Institute of Information Science, Academia Sinica, Taiwan, in January 1995, where he is currently a Research Fellow. His research interests include wavelet analysis, signal and image processing, and multimedia transmission. He obtained the distinguished young researcher award in Taiwan, 2001. He is currently an associated editor of International Journal on Wavelets, Multiresolution and Information Processing. His paper coauthored with Stephane Mallat, "Singularity Detection and Processing with Wavelets," published in IEEE Transactions on Information Theory in 1992, has become a classic paper in wavelet signal processing field.