Simultaneous Image Fusion and Denoising based on Multi-Scale Transform and Sparse Representation
Автор: Tahiatul Islam, Sheikh Md. Rabiul Islam, Xu Huang, Keng Liang Ou
Журнал: International Journal of Image, Graphics and Signal Processing(IJIGSP) @ijigsp
Статья в выпуске: 6 vol.9, 2017 года.
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Multi-scale transform (MST) and sparse representation (SR) techniques are used in an image representation model. Image fusion is used especially in medical, military and remote sensing areas for high resolution vision. In this paper an image fusion technique based on shearlet transformation and sparse representation is proposed to overcome the natural defects of both MST and SR based methods. The proposed method is also used in different transformations and SR for comparison purposes. This research also investigate denoising techniques with additive white Gaussian noise into source images and perform threshold for de-noised into the proposed method. The image quality assessments for the fused image are used for the performance of proposed method and compared with others.
Image fusion, MST, SR, image de-noising, Shearlet
Короткий адрес: https://sciup.org/15014196
IDR: 15014196
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