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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 51–100 of 150 papers

TitleStatusHype
Two-Step Color-Polarization Demosaicking Network—0
Joint demosaicing and fusion of multiresolution coded acquisitions: A unified image formation and reconstruction methodCode1
Residual Swin Transformer Channel Attention Network for Image Demosaicing—0
CRISPnet: Color Rendition ISP Net—0
A Differentiable Two-stage Alignment Scheme for Burst Image Reconstruction with Large ShiftCode1
PyNET-QxQ: An Efficient PyNET Variant for QxQ Bayer Pattern Demosaicing in CMOS Image SensorsCode0
Adaptive Cross-Layer Attention for Image RestorationCode1
Two-Stage is Enough: A Concise Deep Unfolding Reconstruction Network for Flexible Video Compressive SensingCode1
Adaptive Deep PnP Algorithm for Video Snapshot Compressive ImagingCode1
Procedural Kernel Networks—0
Formulating Event-based Image Reconstruction as a Linear Inverse Problem with Deep Regularization using Optical FlowCode1
Snapshot HDR Video Construction Using Coded Mask—0
CDLNet: Noise-Adaptive Convolutional Dictionary Learning Network for Blind Denoising and DemosaicingCode1
Deep Joint Demosaicing and High Dynamic Range Imaging within a Single Shot—0
Real-time division-of-focal-plane polarization imaging system with progressive networks—0
Raw Bayer Pattern Image Synthesis for Computer Vision-oriented Image Signal Processing Pipeline Design—0
Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration—0
Dynamic Attentive Graph Learning for Image RestorationCode1
Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction—0
High-dimensional Assisted Generative Model for Color Image RestorationCode0
Hy-demosaicing: Hyperspectral blind reconstruction from spectral subsamplingCode0
Del-Net: A Single-Stage Network for Mobile Camera ISP—0
End-to-End Learning for Joint Image Demosaicing, Denoising and Super-ResolutionCode1
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images—0
Beyond Joint Demosaicking and Denoising: An Image Processing Pipeline for a Pixel-bin Image SensorCode1
Learning to Jointly Deblur, Demosaick and Denoise Raw Images—0
PyNET-CA: Enhanced PyNET with Channel Attention for End-to-End Mobile Image Signal ProcessingCode1
Memory-Efficient Network for Large-scale Video Compressive SensingCode1
Pre-demosaic Graph-based Light Field Image Compression—0
Joint Denoising and Demosaicking with Green Channel Prior for Real-world Burst ImagesCode1
Plug-and-Play Algorithms for Video Snapshot Compressive ImagingCode1
Joint Demosaicking and Denoising in the Wild: The Case of Training Under Ground Truth Uncertainty—0
Projected Distribution Loss for Image EnhancementCode0
Color Image Restoration Exploiting Inter-channel Correlation with a 3-stage CNNCode0
Learning to Sample the Most Useful Training Patches from Images—0
AIM 2020 Challenge on Learned Image Signal Processing PipelineCode1
Joint Demosaicking and Denoising Benefits from a Two-stage Training Strategy—0
Plug-and-Play Image Restoration with Deep Denoiser PriorCode1
Monochrome and Color Polarization Demosaicking Using Edge-Aware Residual Interpolation—0
An Adaptive Neural Network for Unsupervised Mosaic Consistency Analysis in Image ForensicsCode1
Joint Demosaicing and Denoising With Self GuidanceCode1
Pyramid Attention Networks for Image RestorationCode1
A Review of an Old Dilemma: Demosaicking First, or Denoising First?—0
Moire Image Restoration using Multi Level Hyper Vision NetCode0
Gradient-based Feature Extraction From Raw Bayer Pattern Images—0
Replacing Mobile Camera ISP with a Single Deep Learning ModelCode1
A Sparse Representation Based Joint Demosaicing Method for Single-Chip Polarized Color Sensor—0
Neural Network Generalization: The impact of camera parameters—0
Fully Trainable and Interpretable Non-Local Sparse Models for Image RestorationCode1
CURL: Neural Curve Layers for Global Image EnhancementCode0
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