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Demosaicking
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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
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이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Seeing like a Cephalopod: Colour Vision with a Monochrome Event Camera
PIDSR: Complementary Polarized Image Demosaicing and Super-Resolution
Examining Joint Demosaicing and Denoising for Single-, Quad-, and Nona-Bayer Patterns
Multispectral Demosaicing via Dual Cameras
Fractal-IR: A Unified Framework for Efficient and Scalable Image Restoration
Frequency Enhancement for Image Demosaicking
Binarized Mamba-Transformer for Lightweight Quad Bayer HybridEVS Demosaicing
Generative Model-Assisted Demosaicing for Cross-multispectral Cameras
Learning Joint Denoising, Demosaicing, and Compression from the Raw Natural Image Noise Dataset
Unveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolution
MambaSCI: Efficient Mamba-UNet for Quad-Bayer Patterned Video Snapshot Compressive Imaging
Combining Pre- and Post-Demosaicking Noise Removal for RAW Video
Retinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement
Efficient Polarization Demosaicking via Low-cost Edge-aware and Inter-channel Correlation
How to Best Combine Demosaicing and Denoising?
A self-supervised and adversarial approach to hyperspectral demosaicking and RGB reconstruction in surgical imaging
Learning deep illumination-robust features from multispectral filter array images
Learning Binary Color Filter Arrays with Trainable Hard Thresholding
DemosaicFormer: Coarse-to-Fine Demosaicing Network for HybridEVS Camera
Deep convolutional demosaicking network for multispectral polarization filter array
A New Multi-Picture Architecture for Learned Video Deinterlacing and Demosaicing with Parallel Deformable Convolution and Self-Attention Blocks
Event Camera Demosaicing via Swin Transformer and Pixel-focus Loss
Toward Accurate and Temporally Consistent Video Restoration from Raw Data
Efficient and Accurate Hyperspectral Image Demosaicing with Neural Network Architectures
A Joint Multi-Gradient Algorithm for Demosaicing Bayer Images
Pixel-Inconsistency Modeling for Image Manipulation Localization
Joint Demosaicing and Denoising with Double Deep Image Priors
Iterative Reweighted Least Squares Networks With Convergence Guarantees for Solving Inverse Imaging Problems
Efficient Unified Demosaicing for Bayer and Non-Bayer Patterned Image Sensors
Unsupervised Spectral Demosaicing with Lightweight Spectral Attention Networks
Learning Degradation-Independent Representations for Camera ISP Pipelines
Double Binnable RGB, RGBW and LMS Color Filter Arrays
Model-based demosaicking for acquisitions by a RGBW color filter array
ISP meets Deep Learning: A Survey on Deep Learning Methods for Image Signal Processing
Toward Moiré-Free and Detail-Preserving Demosaicking
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