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 …

This paper proposes a regularized blind deconvolution method for restoring Poissonian
blurred image. The problem is formulated by utilizing the L 0-norm of image gradients and …

Blind image deconvolution plays a very important role in the fields such as astronomical
observation and fluorescence microscopy imaging, in which the noise follows Poisson …

Infrared spectral super-resolution has achieved great success for spectral signals under the
noise-free case. However, the random noise and band overlap restricted the super …

L 0 regularization is highly suitable for estimating the latent image in the blur kernel
estimation step of the two-step process of blind image deblurring. To tackle L 0 …

Denoising images subjected to Gaussian and Poisson noise has attracted attention in many
areas of image processing. This paper introduces an image denoising framework using …

Hyperspectral images are often unavoidably degraded by blur and noise in the acquisition
process, which influences subsequent image processing and analysis. Under the maximum …

Poisson image deblurring, which aims to restore the latent image from its blurred and noisy
observation, has drawn significant attention in image processing. Due to its ill-posed nature …

This paper considers a variational model for restoring images from blurry and speckled
observations. This model utilizes the favorable properties of framelet regularization (eg, the …

Infrared small target detection plays an important role in infrared search and tracking
systems applications. It is difficult to perform target detection when only a single image with …