Multi-scale exposure fusion is an effective image enhancement technique for a high dynamic range (HDR) scene. In this paper, a new multi-scale exposure fusion algorithm is proposed to merge differently exposed low dynamic range (LDR) images by using the weighted guided image filter to smooth the Gaussian pyramids of weight maps for all the LDR images. Details in the brightest and darkest regions of the HDR scene are preserved better by the proposed algorithm without relative brightness change in the fused image. In addition, a new weighted structure tensor is introduced to the differently exposed images and it is adopted to design a detail extraction component for the proposed fusion algorithm, such that users are allowed to manipulate fine details in the enhanced image according to their preference. The proposed multi-scale exposure fusion algorithm is also applied to design a simple single image brightening algorithm for both low-light imaging and back-light imaging.
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http://dx.doi.org/10.1109/TIP.2017.2651366 | DOI Listing |
Bioprocess Biosyst Eng
December 2024
Department of Biological Engineering, Inha University, 100 Inha-Ro, Nam-Gu, Incheon, 22212, Republic of Korea.
Experimental models for exploring abnormal brain blood vessels, including ischemic stroke, are crucial in neuroscience; recently, significant attention has been paid to artificial tissues through tissue engineering. Nanofibers, although commonly used as tissue engineering scaffolds, undergo structural deformations easily, making it challenging to create uniform tissue, especially for the smallest-diameter ones such as perforating arteries. This study focused on the development of a platform capable of reconstructing structurally and functionally replicated perforating arteries.
View Article and Find Full Text PDFQuant Imaging Med Surg
December 2024
Department of Radiation Oncology, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China.
Background: Low-dose computed tomography (LDCT) reduces radiation exposure, but the introduced noise and artifacts impair its diagnostic accuracy. Convolutional neural networks (CNNs) are widely used for LDCT denoising, but they suffer from a limited receptive field. The use of a larger kernel size can enlarge the receptive field and boost model performance; however, the computational cost of the model greatly increases.
View Article and Find Full Text PDFSmall
December 2024
Brazilian Synchrotron Light Laboratory (LNLS), Brazilian Center for Research in Energy and Materials (CNPEM), Campinas, São Paulo, 13083-970, Brazil.
Upon exposure to biological environments, nanoparticles are rapidly coated with biomolecules, predominantly proteins, which alter their colloidal stability, biodistribution, and cell interactions. Despite extensive efforts to investigate the nanoparticles' fate, only a few studies use high-resolution characterization methods that allow in-depth characterization, and the existing methodologies are unable to differentiate particles internalized at the onset of incubation from those taken up toward the end of an incubation period. In this study, these limitations related to incubation disparities are overcame and precisely monitored the spatiotemporal displacement of colloidally stable protein corona-coated nanoparticles within cells.
View Article and Find Full Text PDFAnn Biomed Eng
December 2024
School of Biomedical Engineering, University of Oklahoma, Norman, OK, 73019, USA.
PLoS Comput Biol
December 2024
Université Paris Cité, IAME, INSERM, F-75018 Paris, France.
Households are a major driver of transmission of acute respiratory viruses, such as SARS-CoV-2 or Influenza. Until now antiviral treatments have mostly been used as a curative treatment in symptomatic individuals. During an outbreak, more aggressive strategies involving pre- or post-exposure prophylaxis (PrEP or PEP) could be employed to further reduce the risk of severe disease but also prevent transmission to household contacts.
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