Neighborhood normalized gradient and neighborhood standard deviation-based multi-focus image fusion method

The invention relates to a neighborhood normalized gradient and neighborhood standard deviation-based multi-focus image fusion method. The method comprises the following steps of: firstly, performing multi-scale decomposition on images by using wavelet transform to acquire low-frequency and high-frequency information of the images under different resolutions and different directions; secondly, processing the images by adopting different fusion rules according to the respective characteristics of the low-frequency and high-frequency information, wherein a neighborhood normalized gradient-based fusion method is adopted for the low-frequency sub images to overcome the defect that the traditional low-frequency component fusion method neglects edge information, and a neighborhood standard deviation-based fusion method is adopted for the high-frequency sub images so as to furthest keep detailed information of the images; and finally, performing wavelet reconstruction to acquire a fused image. The method overcomes of edge distortion of the traditional fusion algorithm, obviously improves the quality and the definition of the fused image, and can be applied to various military or civil multi-focus image fusion systems.