Image Fusion Based on the Second Generation Curvelet Transform and Feature Product

This paper puts forward a new image fusion method based on the second generation Curvelet and feature product.Firstly, the fast discrete Curvelet transform is performed on the original images to obtain the coefficients at the corresponding scale.Then the corresponding subband images by using different rules are fused to get the Curvelet coefficient.At last, the resulting image is obtained by inverse Curvelet transform.The new method was tested by multi-foucs images and multi-spectral images.The standard deviation, average gradient and comentropy are used to evaluate the experimental results.And comparisons with the results based on wavelet transform are also carried out.The test results show that the resulting images based on the second generation Curvelet transform are more clear and better.