ArticlePloS one2018
A multi-focus image fusion method via region mosaicking on Laplacian pyramids.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Design of a binocular multispectral stereo imaging system and its application in plant phenotyping.Plant phenomics (Washington, D.C.) · 2025Article
- Multi-focused image fusion algorithm based on multi-scale hybrid attention residual network.PloS one · 2024Article
- General Image Fusion for an Arbitrary Number of Inputs Using Convolutional Neural Networks.Sensors (Basel, Switzerland) · 2022Article
- Combining Regional Energy and Intuitionistic Fuzzy Sets for Infrared and Visible Image Fusion.Sensors (Basel, Switzerland) · 2021Article
- Multi-Focus Image Fusion Method Based on Multi-Scale Decomposition of Information Complementary.Entropy (Basel, Switzerland) · 2021Article
- Fast Multi-Focus Fusion Based on Deep Learning for Early-Stage Embryo Image Enhancement.Sensors (Basel, Switzerland) · 2021Article
- Hybrid Sharpening Transformation Approach for Multifocus Image Fusion Using Medical and Nonmedical Images.Journal of healthcare engineering · 2021Article
- Automated Drawing Tube (Camera Lucida) Method in Light Microscopy Images Analysis Can Comes True.Journal of microscopy and ultrastructureArticle
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Authors and funding
6 authors.
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Abstract
In this paper, a method named Region Mosaicking on Laplacian Pyramids (RMLP) is proposed to fuse multi-focus images that is captured by microscope. First, the Sum-Modified-Laplacian is applied to measure the focus of multi-focus images. Then the density-based region growing algorithm is utilized to segment the focused region mask of each image. Finally, the mask is decomposed into a mask pyramid to supervise region mosaicking on a Laplacian pyramid. The region level pyramid keeps more original information than the pixel level. The experiment results show that RMLP has best performance in quantitative comparison with other methods. In addition, RMLP is insensitive to noise and can reduces the color distortion of the fused images on two datasets.
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