Open AccessAdaptive decomposition method for multi‐modal medical image fusion
Author(s) -
Wang Jing,
Li Xiongfei,
Zhang Yan,
Zhang Xiaoli
Publication year - 2018
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2017.1067
Subject(s) - image fusion , smoothing , artificial intelligence , image (mathematics) , distortion (music) , image texture , pattern recognition (psychology) , fusion , computer science , computer vision , mathematics , image processing , amplifier , computer network , linguistics , philosophy , bandwidth (computing)
In traditional image fusion, source images are separated into a fixed space. The low‐frequency part and the high‐frequency part are not discriminated according to the nature of the image. Traditional fusion rules often use a fixed proportion, causing colour distortion. In this study, a new adaptive decomposition algorithm is proposed to distinguish high frequency and low frequency of structure image to obtain smoothing layer and texture layer. The smoothing layer of the structural image and the colour information of the function image are fused according to dynamic rules, and then the texture layer is added. On the basis of the objective evaluation metrics, the spectral information evaluation metrics are introduced to evaluate the retention of colour. In the experiments, the proposed method is compared with other six classical image fusion methods. The experiment results show that the proposed method can retain the colour information and structure information very well at the same time. Concerning subjective and objective evaluation, the proposed algorithm is superior to other algorithms.