Abstract
As for low resolution of remote sensing images, a novel image fusion algorithm by adaptive PCNN was proposed. The multi-spectral image is firstly converted from RGB to lαβ color space. Then, the input images are adaptively decomposed by simplifying traditional PCNN model and defining image definition as the coupled joint coefficient. The largest entropy ignition time series are finally sent to decision factor to achieve the ultimate fusion image. The experimental results show that the proposed method can not only solve the difficult problem about how to set traditional PCNN parameters adaptively, but also on subjective and objective evaluation, its fusion effect on subjective and objective performance evaluation is better than that of other multi-resolution fusion algorithms such as wavelet transform.
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Li, Y., Wang, K., Chen, Dk. (2010). Multispectral and Panchromatic Images Fusion by Adaptive PCNN. In: Boll, S., Tian, Q., Zhang, L., Zhang, Z., Chen, YP.P. (eds) Advances in Multimedia Modeling. MMM 2010. Lecture Notes in Computer Science, vol 5916. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-11301-7_15
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DOI: https://doi.org/10.1007/978-3-642-11301-7_15
Publisher Name: Springer, Berlin, Heidelberg
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