Demosaicking is the process of reconstructing a full-resolution color image from the sampled
data acquired by a digital camera that apply a color filter array to a single sensor. This paper …

Imaging in low light is challenging due to low photon count and low SNR. Short-exposure
images suffer from noise, while long exposure can lead to blurry images and is often …

Demosaicking and denoising are the key first stages of the digital imaging pipeline but they
are also a severely ill-posed problem that infers three color values per pixel from a single …

The motivation of this paper is to provide an overview of the most recent trends and of the
future research directions in color image and video processing. Rather than covering all …

Deep learning has recently been applied with impressive results to extreme low-light
imaging. Despite the success of single-image processing, extreme low-light video …

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

Deep learning-based image denoising approaches have been extensively studied in recent
years, prevailing in many public benchmark datasets. However, the stat-of-the-art networks …

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

Use of optical imaging for medical and scientific applications requires accurate
quantification of features such as object size, color, and brightness. High pixel density …

This paper introduces deformable convolution in deep learning based joint denoising and
demosaicing (JDD), which yields more adaptable representation and larger receptive fields …