Deep learning for camera data acquisition, control, and image estimation

DJ Brady, L Fang, Z Ma - Advances in Optics and Photonics, 2020 - opg.optica.org
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 review of an old dilemma: Demosaicking first, or denoising first?

Q **, G Facciolo, JM Morel - proceedings of the IEEE/CVF …, 2020 - openaccess.thecvf.com
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 …

Beyond color difference: Residual interpolation for color image demosaicking

D Kiku, Y Monno, M Tanaka… - IEEE Transactions on …, 2016 - ieeexplore.ieee.org
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 …

A practical one-shot multispectral imaging system using a single image sensor

Y Monno, S Kikuchi, M Tanaka… - IEEE Transactions on …, 2015 - ieeexplore.ieee.org
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 …

[PDF][PDF] Color image demosaicking via deep residual learning

R Tan, K Zhang, W Zuo, L Zhang - Proc. IEEE Int. Conf …, 2017 - comp.polyu.edu.hk
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 …

DeepDemosaicking: Adaptive image demosaicking via multiple deep fully convolutional networks

DS Tan, WY Chen, KL Hua - IEEE Transactions on Image …, 2018 - ieeexplore.ieee.org
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 …

Learning deep convolutional networks for demosaicing

NS Syu, YS Chen, YY Chuang - arxiv preprint arxiv:1802.03769, 2018 - arxiv.org
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 …

Adaptive residual interpolation for color and multispectral image demosaicking

Y Monno, D Kiku, M Tanaka, M Okutomi - Sensors, 2017 - mdpi.com
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 …

An adaptive neural network for unsupervised mosaic consistency analysis in image forensics

Q Bammey, RG Gioi, JM Morel - Proceedings of the IEEE …, 2020 - openaccess.thecvf.com
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 …

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 …