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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 101–150 of 150 papers

TitleStatusHype
Merging-ISP: Multi-Exposure High Dynamic Range Image Signal Processing—0
Model-based demosaicking for acquisitions by a RGBW color filter array—0
Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolution—0
Monochrome and Color Polarization Demosaicking Using Edge-Aware Residual Interpolation—0
MSFA-Frequency-Aware Transformer for Hyperspectral Images Demosaicing—0
Multispectral snapshot demosaicing via non-convex matrix completion—0
Multispectral Demosaicing via Dual Cameras—0
NeRD: Neural field-based Demosaicking—0
Neural Network Generalization: The impact of camera parameters—0
NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge—0
Optimizing Codes for Source Separation in Color Image Demosaicing and Compressive Video Recovery—0
Color filter array demosaicking using densely connected residual network.—0
Pixel-Inconsistency Modeling for Image Manipulation Localization—0
CFA Bayer image sequence denoising and demosaicking chain—0
CameraNet: A Two-Stage Framework for Effective Camera ISP Learning—0
Preconditioned Plug-and-Play ADMM with Locally Adjustable Denoiser for Image Restoration—0
Pre-demosaic Graph-based Light Field Image Compression—0
Procedural Kernel Networks—0
Double Binnable RGB, RGBW and LMS Color Filter Arrays—0
BLADE: Filter Learning for General Purpose Computational Photography—0
A Brief Survey of Recent Edge-Preserving Smoothing Algorithms on Digital Images—0
Bayer Demosaicking Using Optimized Mean Curvature over RGB channels—0
Deep Joint Demosaicing and High Dynamic Range Imaging within a Single Shot—0
Deep Learning Approach for Hyperspectral Image Demosaicking, Spectral Correction and High-resolution RGB Reconstruction—0
Raw Bayer Pattern Image Synthesis for Computer Vision-oriented Image Signal Processing Pipeline Design—0
Real-time division-of-focal-plane polarization imaging system with progressive networks—0
Del-Net: A Single-Stage Network for Mobile Camera ISP—0
Deep demosaicking for multispectral filter arrays—0
Demosaicing and Superresolution for Color Filter Array via Residual Image Reconstruction and Sparse Representation—0
Two-Step Color-Polarization Demosaicking Network—0
A self-supervised and adversarial approach to hyperspectral demosaicking and RGB reconstruction in surgical imaging—0
Discriminative Transfer Learning for General Image Restoration—0
Deep Demosaicing for Edge Implementation—0
Efficient and Accurate Hyperspectral Image Demosaicing with Neural Network Architectures—0
Residual Contrastive Learning for Image Reconstruction: Learning Transferable Representations from Noisy Images—0
Efficient Unified Demosaicing for Bayer and Non-Bayer Patterned Image Sensors—0
Enabling ISP-less Low-Power Computer Vision—0
Deep convolutional demosaicking network for multispectral polarization filter array—0
Joint Demosaicking and Denoising Benefits from a Two-stage Training Strategy—0
Examining Joint Demosaicing and Denoising for Single-, Quad-, and Nona-Bayer Patterns—0
Fractal-IR: A Unified Framework for Efficient and Scalable Image Restoration—0
Universal Denoising Networks : A Novel CNN Architecture for Image Denoising—0
Generalized Inpainting Method for Hyperspectral Image Acquisition—0
Residual Swin Transformer Channel Attention Network for Image Demosaicing—0
Generative Model-Assisted Demosaicing for Cross-multispectral Cameras—0
Gradient-based Feature Extraction From Raw Bayer Pattern Images—0
A Review of an Old Dilemma: Demosaicking First, or Denoising First?—0
Aliasing Detection and Reduction in Plenoptic Imaging—0
How to Best Combine Demosaicing and Denoising?—0
Hue Modification Localization By Pair Matching—0
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