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Found 6 papers, 2 papers with code
Multimodal Image Super-resolution via Joint Sparse Representations induced by Coupled Dictionaries
This paper proposes a new approach to construct a high-resolution (HR) version of a low-resolution (LR) image given another HR image modality as reference, based on joint sparse representations induced by coupled dictionaries.
Multi-modal Image Processing based on Coupled Dictionary Learning
In real-world scenarios, many data processing problems often involve heterogeneous images associated with different imaging modalities.
Multimodal Image Denoising based on Coupled Dictionary Learning
The first stage performs joint sparse transform for multimodal images with respect to a group of learned coupled dictionaries, followed by a shrinkage operation on the sparse representations.
Model-inspired Deep Learning for Light-Field Microscopy with Application to Neuron Localization
Light-field microscopes are able to capture spatial and angular information of incident light rays.
Light-Field Microscopy for optical imaging of neuronal activity: when model-based methods meet data-driven approaches
This paper is devoted to a comprehensive survey to state-of-the-art of computational methods for LFM, with a focus on model-based and data-driven approaches.
