Image enhancement is an essential technique used in many imaging applications. The main
motivation of image enhancement is processing an image to be more suitable for specific …

Image enhancement plays an important role in improving image quality in the field of image
processing, which is achieved by highlighting useful information and suppressing redundant …

Under poor illumination, the image information captured by a camera is partially lost, which
seriously affects the visual perception of the human. Inspired by the idea that the fusion of …

Spiking neural networks (SNNs) are a promising energy-efficient alternative to artificial
neural networks (ANNs) due to their rich dynamics, capability to process spatiotemporal …

Low light often leads to poor image visibility, which can easily affect the performance of
computer vision algorithms. First, this paper proposes the absorption light scattering model …

Self-regularized low-light image enhancement does not require any normal-light image in
training, thereby freeing from the chains of paired or unpaired training data that are time …

Most existing multi-modal image fusion methods require multi-scale transforms. However,
this requirement does not necessarily lead to the fusion result containing the original …

Satellite images normally possess relatively narrow brightness value ranges necessitating
the requirement for contrast stretching, preserving the relevant details before further image …

To solve the problem of simultaneously estimating the illumination and reflectance (IR) from
a single image based on the Retinex theory, an effective way is utilizing a Maximum-a …

Satellite images usually have relatively narrow brightness value ranges which entails a
demand to broaden the contrast and retain relevant details contained in the images prior to …