Fusion algorithm of hyperspectral image based on the second generation wavelet transform and PCNN
LI Wan-chen, CHEN Han-zi(School of Information and Communication, Harbin Engineering University, Harbin 150001, China)
Fusion technology was an effective way to reduce the difficulty of imagert processing. Here, a new fusion algorithm based on the second generation wavelet transform and pulse-coupled neural networks (PCNN) was proposed. After divided the whole data space into several subspaces by adaptive subspace decomposition technology, each band image was decomposed into low frequency coefficient and high frequency coefficient by the second generation wavelet transform. Then the low frequency coefficient was weighted fused according to the standard deviation of each image, and in the high parts, use the global coupling and pulse synchronization characteristics of PCNN to choose high frequency coefficients. The result of the fusion experiment based on the real hyperspectral data showed :the new algorithm can get satisfied fusion effects,and the result is better than the fusion algorithms that use the first generation wavelet or the second generation wavelet singly.
【CateGory Index】： TP751