Multi-morphological Fusion of Medical Image and Performance Evaluation based on Wavelet Transform

We choosed multi-focus images and standard MRI / CT gray images for source images and applied the following strategies to decomposition and fusion. On the one hand,decomposition of low frequency and high frequency wavelet coefficients was adopted with single scale and multi-scale way. On the other hand,image fusion region was selected by independent pixel and neighborhood operation. Through above different operation of decomposition and fusion,the fusion image of different fusion rule was obtained. Based on the fusion image of different fusion rule,the influences of various fusion rules on the fusion results were compared and analyzed,which was the purpose of this paper. By means of analyzing the experimental results and evaluation results of multi-focus fusion images and clinical MRI / CT fusion images. It show that neighborhood filtering operation can greatly improve the result of image fusion and make the detail of the image information more rich; multi-scale decompose can increase the brightness of the fusion image with respect to single scale decompose.