Publication Type : Journal Article
Source : Journal of Engineering Science and Technology, pp. 1231 - 1247, Vol. 14(3), June 2019.
Url : https://jestec.taylors.edu.my/Vol%2014%20issue%203%20June%202019/14_3_9.pdf
Campus : Chennai
School : School of Engineering
Department : Computer Science and Engineering
Year : 2019
Abstract : Image fusion schemes are desirable to obtain a high-quality image by integrating complementary information from multiple source images. The main aim of this paper is to propose a novel image fusion technique that provides a highly informative image, which is useful in various applications like computer vision, medical diagnosis, remote sensing, etc. Traditional Sparse Representation (SR) based fusion method makes use of a single highly redundant dictionary for image fusion. This increases complexity and may also lead to visual artefacts in the fused image. Fusion scheme using dictionary-based sparse representation is proposed in this paper. A large number of image patches are pre-classified based on projections using R-Transform and a set of compact sub-dictionaries are learnt from them. At the fusion stage, one of the sub-dictionaries is chosen to fuse the given set of source images. Quantitative and Qualitative evaluation of the proposed fusion scheme on multi-focus and multi-modal images shows the superiority of the proposed scheme over other existing fusion algorithms.
Cite this Research Publication : K. Ashwini and R. Amutha, “Sparse based image fusion using Compact Sub-dictionaries”, Journal of Engineering Science and Technology, pp. 1231 - 1247, Vol. 14(3), June 2019.