Compared to DSLR cameras, smartphone cameras have smaller sensors, which limits their
spatial resolution; smaller apertures, which limits their light gathering ability; and smaller …

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 …

Usually located at the very early stages of the computational photography pipeline,
demosaicing and denoising play important parts in the modern camera image processing …

A division-of-focal-plane or microgrid image polarimeter enables us to acquire a set of
polarization images in one shot. Since the polarimeter consists of an image sensor …

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 …

Snapshot polarization imaging has gained interest in the last few decades. Recent research
and technology achievements defined the polarization Filter Array (PFA). It is dedicated to …

The hyperspectral image (HSI) denoising has been widely utilized to improve HSI qualities.
Recently, learning-based HSI denoising methods have shown their effectiveness, but most …

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 …

Denoising (DN) and demosaicing (DM) are the first crucial stages in the image signal
processing pipeline. Recently, researches pay more attention to solve DN and DM in a joint …