Image fusion algorithm based on block-DCT in wavelet domain
基于分块DCT变换编码的小波域多幅图像融合算法

A feature-level image fusion algorithm using wavelet transform combined with the discrete cosine transform (DCT) is proposed. The basic idea is to perform block-DCT of each source image first, and then to select the retained coefficients according to maximum variance; each image is compressed to 25 percent of the original size. The coordinates of the retained coefficients are used as private keys. Finally, the processed DCT coefficient matrixes are taken as the wavelet coefficients and the fused image is obtained by taking the inverse wavelet transform. The experimental results show that the algorithm realizes the fusion of images with different sizes. Furthermore, one single image can be reconstructed by one single private key.