4.7 Article

Binlets: Data fusion-aware denoising enables accurate and unbiased quantification of multichannel signals

Related references

Note: Only part of the references are listed.
Review Automation & Control Systems

On wavelet-based statistical process monitoring

Achraf Cohen et al.

Summary: This paper provides an overview of wavelet-based statistical process monitoring techniques, focusing on wavelet statistical properties, control charts based on wavelet coefficients, and wavelet-based process monitoring methods within a machine learning framework. The use of wavelets is widely seen in multivariate methods compared to univariate methods, with potential research areas identified in image process monitoring and designing control charts based on wavelet statistics.

TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL (2022)

Article Biochemistry & Molecular Biology

Imaging in focus: An introduction to denoising bioimages in the era of deep learning

Romain F. Laine et al.

Summary: Fluorescence microscopy enables direct observation of hidden dynamic processes of life, but image noise can complicate interpretation. Deep learning methods have emerged as successful approaches for denoising, providing a powerful content-aware solution.

INTERNATIONAL JOURNAL OF BIOCHEMISTRY & CELL BIOLOGY (2021)

Review Computer Science, Artificial Intelligence

Image denoising review: From classical to state-of-the-art approaches

Bhawna Goyal et al.

INFORMATION FUSION (2020)

Review Computer Science, Interdisciplinary Applications

Brief review of image denoising techniques

Linwei Fan et al.

VISUAL COMPUTING FOR INDUSTRY BIOMEDICINE AND ART (2019)

Review Computer Science, Artificial Intelligence

Denoising of Microscopy Images: A Review of the State-of-the-Art, and a New Sparsity-Based Method

William Meiniel et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2018)

Article Computer Science, Artificial Intelligence

Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoising

Kai Zhang et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2017)

Article Chemistry, Analytical

pawFLIM: reducing bias and uncertainty to enable lower photon count in FLIM experiments

Mauro Silberberg et al.

METHODS AND APPLICATIONS IN FLUORESCENCE (2017)

Article Computer Science, Information Systems

Skellam Shrinkage: Wavelet-Based Intensity Estimation for Inhomogeneous Poisson Data

Keigo Hirakawa et al.

IEEE TRANSACTIONS ON INFORMATION THEORY (2012)

Letter Computer Science, Artificial Intelligence

A Closed-Form Approximation of the Exact Unbiased Inverse of the Anscombe Variance-Stabilizing Transformation

Markku Makitalo et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2011)

Article Computer Science, Artificial Intelligence

Practical Poissonian-Gaussian noise modeling and fitting for single-image raw-data

Alessandro Foi et al.

IEEE TRANSACTIONS ON IMAGE PROCESSING (2008)