A NEW STRATEGY TO IMPROVE IMAGE FUSION EFFECT

摘要：

The purpose of image fusion is to combine information from several different source images to one image, which becomes reliable and much easier to be comprehended by people. Based on analyzing the relations of average and standard deviation of the two or more source images, a new strategy to improve image fusion effect and a new evaluation measure named RAS (the ratio between average and standard deviation) are proposed in this paper. We apply wavelet transform to decompose an image into low-frequency sub-image and high-frequency sub-images and apply different fusion rules respectively to low-frequency sub-image and high-frequency sub-images. According to subjective evaluation and objective criteria, such as entropy, root mean square error (RMSE), peak-to-peak signal-to-noise ratio (PSNR),RAS, the proposed strategy is very effective and universal to some extent for fusing a class of images whose average and standard deviation are approximately equal respectively through extensive experiments.

关键词： Image fusion Wavelet transform Multi-Resolution (MR) RAS

作者: JIAN-WEI LIU QIAN YIN PING GUO

作者单位: Image Processing and Pattern Recognition Laboratory, Beijing Normal University, Beijing 100875, China

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 3770-3775

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）