INTELLIGENT FUSION FOR METEOROLOGICAL NEPHOGRAM PROCESSING
As known, meteorological nephogram processing is very complicated due to complex environment, various sampling methods, and algorithm differences. For multi-resolution image data of nephogram, fusion is relatively useful; however, it is hard to simulate the human ability of image fusion. Based on review of researches on psychophysics and physiology of human vision, this paper presents an effective multi-resolution image data fusion methodology, previously discrete Wavelet was used to decompose and reconstruct image details. To simulate images recognition and understanding procedure implemented in the human vision system, ordinary Kriging algorithm is introduced to create grey-scale based grids. Through the two-dimensional Wavelet Transform, original images can be decomposed into different types of details and levels, while multiple grids can be unified as a series of key points with corresponding grey-scale, they are composed back by inverse wavelet network. As an example, the model is applied to meteorological nephogram, which proves the effectiveness of the proposed model.
Image Fusion Nephogram Processing Kriging Algorithm Wavelet Transform
Q.P.ZHANG L.L.LAI
School of Engineering and Mathematical Sciences, City University London, UK
国际会议
2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)
昆明
英文
3874-3877
2008-07-12（万方平台首次上网日期，不代表论文的发表时间）