Image Mosaic Based on Stationary Wavelet Decomposition and Energy Function Optimization
基于静态小波分解和能量函数优化的图像拼接

A novel method for image mosaics based on stationary wavelet decomposition and energy function optimization was presented.First,stationary wavelet decomposition and series similarity detection were used for searching the corresponding points in high frequency images.Then delicate search were made in origin image for exact matching based on these corresponding points.Fusion factors for high frequency detail images were calculated from energy function that contains image gradient, while linear weight function were used for low frequency smooth image.This conquers the blur and mackle problems in the overlap area using traditional linear weight function.Experiment results show that satisfying visual effect can be achieved using this method while matching time is also reduced in image mosaics.