Noise type and strength estimation are important in many image processing applications like
denoising, compression, video tracking, etc. There are many existing methods for estimation …

We propose a non-iterative image deconvolution algorithm for data corrupted by Poisson or
mixed Poisson-Gaussian noise. Many applications involve such a problem, ranging from …

We propose a two-step algorithm that automatically estimates the noise level function of
stationary noise from a single image, ie, the noise variance as a function of the image …

Digital camera noise information is useful in various applications: image enhancement and
postprocessing, device selection for a particular system, recognition, decision making, and …

Deconvolution is widely used to improve the contrast and clarity of a 3D focal stack collected
using a fluorescence microscope. But despite being extensively studied, deconvolution …

The additive white Gaussian noise (AWGN) model is ubiquitous in signal processing. This
model is often justified by central-limit theorem (CLT) arguments. However, whereas the CLT …

Investigation of nuclear lamina architecture relies on superresolved microscopy. However,
epitope accessibility, labeling density, and detection precision of individual molecules pose …

Noise estimation for image sensor is a key technique in many image pre-processing
applications such as blind de-noising. The existing noise estimation methods for additive …

With the widespread internet usage, digital contents are easily distributed throughout the
world. To eliminate concerns of producers and owners of digital contents, watermarking …

An accurate quantitative noise estimate is required in many image/video processing
applications like denoising, computer vision, pattern recognition and tracking. But blind and …