To make the face hallucination process robust to impulse noise, a new outlier elimination
based iterative neighbor representation (OEINR) algorithm is proposed in this work. The …

Face super-resolution (SR) is the task of generating high-resolution (HR) face images from
the low-resolution (LR) inputs. Recently, deep learning-based methods have shown …

A new low-light robust face super-resolution (SR) model via morphological transformation-
based locality-constrained representation (MTLcR) is proposed to improve the robustness of …

Face super-resolution (FSR) has recently become an interesting topic of study in the fields of
image processing and computer vision. However, current FSR methods are still incapable of …

Over the past few decades, there has been a lot of advancement in face hallucination (or
super-resolution) technologies, with the position-patch-based locality constrained methods …

A robust watermarking scheme using an optimization-based image reconstruction technique
is presented in this paper. In the proposed scheme, the cover image (CI) and watermark …

Deep learning techniques in electronic surveillance have shown impressive performance for
super-resolution (SR) of captured low-quality face images. Most of these techniques adopt …

This paper proposes the BLUR & TRACK system that anonymizes detected face based on
blurring algorithm and supports efficient retrieval of the specified human face recorded in the …

This paper proposes a learning-based image noise level prediction technique based on
Gaussian process regression (GPR). The proposed work is divided into three phases: image …

Deriving a unique cryptographic key from biometric measurements is a challenging task due
to the existing noise gap between the biometric measurements and error correction coding …