Open AccessImage fusion algorithm based on block-DCT in wavelet domain
Author(s) -
Guangming Tian,
Shuai Feng,
Nie Shou-Ping,
Zhuqing Zhu
Publication year - 2011
Publication title -
wuli xuebao
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.199
H-Index - 47
ISSN - 1000-3290
DOI - 10.7498/aps.60.114205
Subject(s) - discrete cosine transform , wavelet , algorithm , image fusion , artificial intelligence , computer science , discrete wavelet transform , pattern recognition (psychology) , image (mathematics) , wavelet transform , inverse , block (permutation group theory) , stationary wavelet transform , feature (linguistics) , mathematics , computer vision , linguistics , philosophy , geometry
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.