Image restoration by learning morphological opening-closing network

DOI10.1515/mathm-2020-0103zbMath1469.68161OpenAlexW3096091382WikidataQ113073559 ScholiaQ113073559MaRDI QIDQ1980895

Bhabatosh Chanda, Moni Shankar Dey, Ranjan Mondal

Publication date: 9 September 2021

Published in: Mathematical Morphology. Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/mathm-2020-0103

zbMATH Keywords

morphological networkde-hazingde-rainingdilation erosion neuronslearning structuring elementopening-closing network

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Computing methodologies for image processing (68U10) Computer graphics; computational geometry (digital and algorithmic aspects) (68U05)

Related Items

Learning grayscale mathematical morphology with smooth morphological layers ⋮ MorphoActivation: generalizing ReLU activation function by mathematical morphology ⋮ Logarithmic morphological neural nets robust to lighting variations ⋮ On some associations between mathematical morphology and artificial intelligence ⋮ Going beyond p-convolutions to learn grayscale morphological operators ⋮ Learnable Empirical Mode Decomposition based on Mathematical Morphology

Uses Software

• GitHub
• U-Net
• MorphoN
• DeconvNet
• Flickr30K
• DnCNN
• FFDNet
• DehazeNet
• AOD-Net

Cites Work

• Unnamed Item
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• A Fast Single Image Haze Removal Algorithm Using Color Attenuation Prior
• DehazeNet: An End-to-End System for Single Image Haze Removal
• Color Balance and Fusion for Underwater Image Enhancement
• Clearing the Skies: A Deep Network Architecture for Single-Image Rain Removal
• Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising
• Single Image Rain Streak Decomposition Using Layer Priors
• Morphological Networks for Image De-raining