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Multi-focus image fusion using local variability

Abstract : In this thesis, we are interested in the multi-focus image fusion method. This technique consists of fusing several captured images with different focal lengths of the same scene to obtain an image with better quality than the two source images. We propose an image fusion method based on Laplacian pyramid technique using Discrete Wavelet Transform (DWT) as a selection rule. We then develop two multi-focus image fusion methods based on the local variability of each pixel. It takes into account the information in the surrounding pixel area. The first method is to use local variability as an information in the Dempster-Shafer theory. The second method uses a metric based on local variability. Indeed, the proposed fusion method weighs each pixel by an exponential of its local variability. A comparative study between the proposed methods and the existing methods was carried out. The experimental results show that our proposed methods give better fusions, both in visual perception and in quantitative analysis.
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Submitted on : Friday, June 22, 2018 - 4:03:00 AM
Last modification on : Friday, July 17, 2020 - 2:59:05 PM
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  • HAL Id : tel-01820628, version 1


Ias Sri Wahyuni. Multi-focus image fusion using local variability. Image Processing [eess.IV]. Université Bourgogne Franche-Comté, 2018. English. ⟨NNT : 2018UBFCK010⟩. ⟨tel-01820628⟩



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