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.