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Demosaicking

Most modern digital cameras acquire color images by measuring only one color channel per pixel, red, green, or blue, according to a specific pattern called the Bayer pattern. Demosaicking is the processing step that reconstruct a full color image given these incomplete measurements.

Source: Revisiting Non Local Sparse Models for Image Restoration

Papers

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Showing 126–150 of 150 papers

TitleStatusHype
Deep Demosaicing for Polarimetric Filter Array CamerasCode0
Moire Image Restoration using Multi Level Hyper Vision NetCode0
PyNET-QxQ: An Efficient PyNET Variant for QxQ Bayer Pattern Demosaicing in CMOS Image SensorsCode0
Consensus Convolutional Sparse CodingCode0
Joint Demosaicking and Denoising by Fine-Tuning of Bursts of Raw ImagesCode0
A New Multi-Picture Architecture for Learned Video Deinterlacing and Demosaicing with Parallel Deformable Convolution and Self-Attention BlocksCode0
A Framework for Fast Image Deconvolution with Incomplete ObservationsCode0
Efficient Polarization Demosaicking via Low-cost Edge-aware and Inter-channel CorrelationCode0
Dirty Pixels: Towards End-to-End Image Processing and PerceptionCode0
Reconfiguring the Imaging Pipeline for Computer VisionCode0
Color Image Restoration Exploiting Inter-channel Correlation with a 3-stage CNNCode0
CURL: Neural Curve Layers for Global Image EnhancementCode0
Joint Multi-Scale Tone Mapping and Denoising for HDR Image EnhancementCode0
Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution PipelineCode0
Binarized Mamba-Transformer for Lightweight Quad Bayer HybridEVS DemosaicingCode0
Learning Binary Color Filter Arrays with Trainable Hard ThresholdingCode0
Deep Mean-Shift Priors for Image RestorationCode0
Learning deep illumination-robust features from multispectral filter array imagesCode0
Learning Joint Denoising, Demosaicing, and Compression from the Raw Natural Image Noise DatasetCode0
Residual Non-local Attention Networks for Image RestorationCode0
Learning Proximal Operators: Using Denoising Networks for Regularizing Inverse Imaging ProblemsCode0
DeepISP: Towards Learning an End-to-End Image Processing PipelineCode0
Deep Image Demosaicking using a Cascade of Convolutional Residual Denoising NetworksCode0
Handheld Multi-Frame Super-ResolutionCode0
Low Cost Edge Sensing for High Quality DemosaickingCode0
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