Papers Demosaicking
“Demosaicking” 태그가 달린 논문 150편 · 필터 해제
NTIRE 2025 the 2nd Restore Any Image Model (RAIM) in the Wild Challenge
In this paper, we present a comprehensive overview of the NTIRE 2025 challenge on the 2nd Restore Any Image Model (RAIM) in the Wild. This challenge established a new benchmark for real-world image restoration, featuring…
DemosaickingDenoisingImage RestorationSeeing like a Cephalopod: Colour Vision with a Monochrome Event Camera
Cephalopods exhibit unique colour discrimination capabilities despite having one type of photoreceptor, relying instead on chromatic aberration induced by their ocular optics and pupil shapes to perceive spectral informa…
DemosaickingPIDSR: Complementary Polarized Image Demosaicing and Super-Resolution
Polarization cameras can capture multiple polarized images with different polarizer angles in a single shot, bringing convenience to polarization-based downstream tasks. However, their direct outputs are color-polarizati…
DemosaickingImage Super-ResolutionSuper-ResolutionExamining Joint Demosaicing and Denoising for Single-, Quad-, and Nona-Bayer Patterns
Camera sensors have color filters arranged in a mosaic layout, traditionally following the Bayer pattern. Demosaicing is a critical step camera hardware applies to obtain a full-channel RGB image. Many smartphones now ha…
DemosaickingDenoisingJoint Demosaicing and DenoisingMultispectral Demosaicing via Dual Cameras
Multispectral (MS) images capture detailed scene information across a wide range of spectral bands, making them invaluable for applications requiring rich spectral data. Integrating MS imaging into multi camera devices, …
DemosaickingFractal-IR: A Unified Framework for Efficient and Scalable Image Restoration
While vision transformers achieve significant breakthroughs in various image restoration (IR) tasks, it is still challenging to efficiently scale them across multiple types of degradations and resolutions. In this paper,…
DeblurringDemosaickingDenoisingGrayscale Image Denoising+4Frequency Enhancement for Image Demosaicking
Recovering high-frequency textures in image demosaicking remains a challenging issue. While existing methods introduced elaborate spatial learning methods, they still exhibit limited performance. To address this issue, a…
DemosaickingBinarized Mamba-Transformer for Lightweight Quad Bayer HybridEVS Demosaicing
Quad Bayer demosaicing is the central challenge for enabling the widespread application of Hybrid Event-based Vision Sensors (HybridEVS). Although existing learning-based methods that leverage long-range dependency model…
Computational EfficiencyDemosaickingEvent-based visionMambaGenerative Model-Assisted Demosaicing for Cross-multispectral Cameras
As a crucial part of the spectral filter array (SFA)-based multispectral imaging process, spectral demosaicing has exploded with the proliferation of deep learning techniques. However, (1) bothering by the difficulty of …
DemosaickingLearning Joint Denoising, Demosaicing, and Compression from the Raw Natural Image Noise Dataset
This paper introduces the Raw Natural Image Noise Dataset (RawNIND), a diverse collection of paired raw images designed to support the development of denoising models that generalize across sensors, image development wor…
Computational EfficiencyDemosaickingDenoisingUnveiling Hidden Details: A RAW Data-Enhanced Paradigm for Real-World Super-Resolution
Real-world image super-resolution (Real SR) aims to generate high-fidelity, detail-rich high-resolution (HR) images from low-resolution (LR) counterparts. Existing Real SR methods primarily focus on generating details fr…
DemosaickingDenoisingImage Super-ResolutionSuper-ResolutionMambaSCI: Efficient Mamba-UNet for Quad-Bayer Patterned Video Snapshot Compressive Imaging
Color video snapshot compressive imaging (SCI) employs computational imaging techniques to capture multiple sequential video frames in a single Bayer-patterned measurement. With the increasing popularity of quad-Bayer pa…
DemosaickingMambaCombining Pre- and Post-Demosaicking Noise Removal for RAW Video
Denoising is one of the fundamental steps of the processing pipeline that converts data captured by a camera sensor into a display-ready image or video. It is generally performed early in the pipeline, usually before dem…
DemosaickingDenoisingRetinex-RAWMamba: Bridging Demosaicing and Denoising for Low-Light RAW Image Enhancement
Low-light image enhancement, particularly in cross-domain tasks such as mapping from the raw domain to the sRGB domain, remains a significant challenge. Many deep learning-based methods have been developed to address thi…
DemosaickingDenoisingExposure CorrectionImage Enhancement+2Efficient Polarization Demosaicking via Low-cost Edge-aware and Inter-channel Correlation
Efficient and high-fidelity polarization demosaicking is critical for industrial applications of the division of focal plane (DoFP) polarization imaging systems. However, existing methods have an unsatisfactory balance o…
CPUDemosaickingHow to Best Combine Demosaicing and Denoising?
Image demosaicing and denoising play a critical role in the raw imaging pipeline. These processes have often been treated as independent, without considering their interactions. Indeed, most classic denoising methods han…
DemosaickingDenoisingA self-supervised and adversarial approach to hyperspectral demosaicking and RGB reconstruction in surgical imaging
Hyperspectral imaging holds promises in surgical imaging by offering biological tissue differentiation capabilities with detailed information that is invisible to the naked eye. For intra-operative guidance, real-time sp…
DemosaickingLearning deep illumination-robust features from multispectral filter array images
Multispectral (MS) snapshot cameras equipped with a MS filter array (MSFA), capture multiple spectral bands in a single shot, resulting in a raw mosaic image where each pixel holds only one channel value. The fully-defin…
DemosaickingImage Augmentationimage-classificationImage ClassificationLearning Binary Color Filter Arrays with Trainable Hard Thresholding
Color Filter Arrays (CFA) are optical filters in digital cameras that capture specific color channels. Current commercial CFAs are hand-crafted patterns with different physical and application-specific considerations. Th…
channel selectionDemosaickingDemosaicFormer: Coarse-to-Fine Demosaicing Network for HybridEVS Camera
Hybrid Event-Based Vision Sensor (HybridEVS) is a novel sensor integrating traditional frame-based and event-based sensors, offering substantial benefits for applications requiring low-light, high dynamic range, and low-…
Data AugmentationDemosaickingEvent-based visionImage Restoration