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A lightweight scheme for multi-focus image fusion
journal contributionposted on 2018-09-01, 00:00 authored by X Jin, Jingyu HouJingyu Hou, R Nie, S Yao, D Zhou, Q Jiang, K He
The aim of multi-focus image fusion is to fuse the images taken from the same scene with different focuses so that we can obtain a resultant image with all objects in focus. However, the most existing techniques in many cases cannot gain good fusion performance and acceptable complexity simultaneously. In order to improve image fusion efficiency and performance, we propose a lightweight multi-focus image fusion scheme based on Laplacian pyramid transform (LPT) and adaptive pulse coupled neural networks-local spatial frequency (PCNN-LSF), and it only needs to deal with fewer sub-images than common methods. The proposed scheme employs LPT to decompose a source image into the corresponding constituent sub-images. Spatial frequency (SF) is calculated to adjust the linking strength β of PCNN according to the gradient features of the sub-images. Then oscillation frequency graph (OFG) of the sub-images is generated by PCNN model. Local spatial frequency (LSF) of the OFG is calculated as the key step to fuse the sub-images. Incorporating LSF of the OFG into the fusion scheme (LSF of the OFG represents the information of its regional features); it can effectively describe the detailed information of the sub-images. LSF can enhance the features of OFG and makes it easy to extract high quality coefficient of the sub-image. The experiments indicate that the proposed scheme achieves good fusion effect and is more efficient than other commonly used image fusion algorithms.
JournalMultimedia tools and applications
Pagination23501 - 23527
LocationNew York, N.Y.
Publication classificationC Journal article; C1 Refereed article in a scholarly journal
Copyright notice2018, Springer
ImageprocessingImage fusionPulse coupled neural networksLaplacian pyramid transformSpatial frequencyScience & TechnologyTechnologyComputer Science, Information SystemsComputer Science, Software EngineeringComputer Science, Theory & MethodsEngineering, Electrical & ElectronicComputer ScienceEngineeringImage processingMANY-CORE PROCESSORSWAVELET TRANSFORMPYRAMID DECOMPOSITIONCONTOURLET TRANSFORMPARALLEL FRAMEWORKNEURAL-NETWORKPCNNLINKINGDOMAINInformation SystemsArtificial Intelligence and Image ProcessingComputer SoftwareDistributed Computing