Multi-source and Multi-feature Image Information Fusion Based on Compressive Sensing
Abstract: Image fusion is a
comprehensive information processing technique and its purpose is to enhance
the reliability of the image via the processing of the redundant data among
multiple images, improve the image definition and information content through
fusion of the complementary information of multiple images so as to obtain the
information of the objective or the scene in a more accurate, reliable and
comprehensive manner. This paper uses the sparse representation method of compressive
sensing theory, proposes a multi-source and multi-feature image information
fusion method based on compressive sensing in accordance with the features of
image fusion, performs sparsification processing on the source image with K-SVD
algorithm and OMP algorithm to transfer from spatial domain to frequency domain
and decomposes into low-frequency part and high-frequency park. Then it fuses
with different fusion rules and the experimental results prove that the method
of this paper is better than the traditional methods and it can obtain better
fusion effects.
Author: Qingzhao Li, Fei Jiang
Journal Code: jptkomputergg160222