Open AccessHybridisation of single‐image super‐resolution with edge‐aware multi‐focus image fusion for edge enrichment
Author(s) -
Gopalakrishnan Sreeja,
Ovireddy Saraniya
Publication year - 2020
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.2020.0527
Subject(s) - artificial intelligence , computer vision , image fusion , focus (optics) , computer science , smoothing , anisotropic diffusion , enhanced data rates for gsm evolution , filter (signal processing) , image resolution , image (mathematics) , pixel , pattern recognition (psychology) , fusion , resolution (logic) , optics , linguistics , philosophy , physics
To break the curtailment of digital imaging and retrieve appropriate information with different focused images, a novel edge‐aware multi‐focus image fusion is proposed by integrating the single‐image super‐resolution (SISR) method along with the edge‐preserving filters. Initially, the multi‐focus images are converted to high resolution images by estimating missing high frequency details from its blurred versions. With acquired high resolution images, smoothing by median and the anisotropic diffusion filters are performed to extract focused regions. An initial weight map is constructed by using maximum selection of pixel intensities of the difference images obtained with filtering. The precision of estimated weight map is further improved by exhibiting morphological operations and guided filter. Finally, the images are fused based on the optimised decision map. Simulation results of proposed fusion work are evaluated with seven metrics and the values are compared with different state‐of‐the‐art methods. Both the quantitative and qualitative analyses showed the excellence of proposed work over other fusion methods.