Deep learning for camera data acquisition, control, and image estimation
We review the impact of deep-learning technologies on camera architecture. The function of
a camera is first to capture visual information and second to form an image. Conventionally …
a camera is first to capture visual information and second to form an image. Conventionally …
A review of an old dilemma: Demosaicking first, or denoising first?
Image denoising and demosaicking are the first two crucial steps in digital camera pipelines.
In most of the literature, denoising and demosaicking are treated as two independent …
In most of the literature, denoising and demosaicking are treated as two independent …
Beyond color difference: Residual interpolation for color image demosaicking
In this paper, we propose residual interpolation (RI) as an alternative to color difference
interpolation, which is a widely accepted technique for color image demosaicking. Our …
interpolation, which is a widely accepted technique for color image demosaicking. Our …
A practical one-shot multispectral imaging system using a single image sensor
Single-sensor imaging using the Bayer color filter array (CFA) and demosaicking is well
established for current compact and low-cost color digital cameras. An extension from the …
established for current compact and low-cost color digital cameras. An extension from the …
[PDF][PDF] Color image demosaicking via deep residual learning
Color demosaicking plays a key role in digital imaging with a color filter array. Most existing
demosaicking methods are based on hand-crafted priors, which may exhibit unpleasant …
demosaicking methods are based on hand-crafted priors, which may exhibit unpleasant …
DeepDemosaicking: Adaptive image demosaicking via multiple deep fully convolutional networks
Convolutional neural networks are currently the state-of-the-art solution for a wide range of
image processing tasks. Their deep architecture extracts low-and high-level features from …
image processing tasks. Their deep architecture extracts low-and high-level features from …
Learning deep convolutional networks for demosaicing
This paper presents a comprehensive study of applying the convolutional neural network
(CNN) to solving the demosaicing problem. The paper presents two CNN models that learn …
(CNN) to solving the demosaicing problem. The paper presents two CNN models that learn …
Adaptive residual interpolation for color and multispectral image demosaicking
Color image demosaicking for the Bayer color filter array is an essential image processing
operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based …
operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based …
An adaptive neural network for unsupervised mosaic consistency analysis in image forensics
Automatically finding suspicious regions in a potentially forged image by splicing, inpainting
or copy-move remains a widely open problem. Blind detection neural networks trained on …
or copy-move remains a widely open problem. Blind detection neural networks trained on …
A two-stage convolutional neural network for joint demosaicking and super-resolution
K Chang, H Li, Y Tan, PLK Ding… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
As two practical and important image processing tasks, color demosaicking (CDM) and
super-resolution (SR) have been studied for decades. However, most literature studies …
super-resolution (SR) have been studied for decades. However, most literature studies …