Multifocus Image Fusion Algorithm Based on Contourlet Decomposition and Region Statistics

A novel multifocus image fusion algorithm based on contourlet transform and region statistics was proposed. For good properties of multiscale, localization, directionality and anisotropy, the multifocus source images are first decomposed using contourlet transform. Fusion operations based on region statistics are implemented for all subbands in each scale and direction. Regional variance and local energy are utilized as the fusion rule in low frequency and high frequency subbands, respectively. Experimental results show that the proposed method can extract image features more effectively and obtain better fusion performance. Compared with traditional gradient pyramid algorithm and wavelet based fusion algorithm, the mean square error of the proposed algorithm is increased by 34.8%and 42.6%.

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