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 …

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 …

Synthetic image generation methods have recently revolutionized the way in which visual
content is created. This opens up creative opportunities but also presents challenges in …

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 …

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 …

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 …

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 …

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 …

As two practical and important image processing tasks, color demosaicking (CDM) and
super-resolution (SR) have been studied for decades. However, most literature studies …

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 …