Journal ArticleDOI
Bayesian-Based Iterative Method of Image Restoration
TLDR
An iterative method of restoring degraded images was developed by treating images, point spread functions, and degraded images as probability-frequency functions and by applying Bayes’s theorem.Abstract:
An iterative method of restoring degraded images was developed by treating images, point spread functions, and degraded images as probability-frequency functions and by applying Bayes’s theorem. The method functions effectively in the presence of noise and is adaptable to computer operation.read more
Citations
More filters
Journal ArticleDOI
Degraded Image Semantic Segmentation With Dense-Gram Networks
TL;DR: A novel Dense-Gram Network is proposed to more effectively reduce the gap than the conventional strategies and segment degraded images and yields state-of-the-art semantic segmentation performance on degraded images synthesized using PASCAL VOC 2012, SUNRGBD, CamVid, and CityScapes datasets.
Journal ArticleDOI
A treatment procedure for VLT/SINFONI data cubes: application to NGC 5643
TL;DR: In this paper, a treatment procedure for data cubes obtained with the Spectrograph for Integral Field Observations in the Near Infrared of the Very Large Telescope (VLIW) was presented.
Journal ArticleDOI
Punching holes in light: recent progress in single-shot coded-aperture optical imaging.
TL;DR: This review comprehensively surveys state-of-the-art single-shot coded-aperture optical imaging and provides two representative examples of active-encoded and passive-encoding approaches, with a particular emphasis on their methodology and applications as well as their advantages and challenges.
Journal ArticleDOI
A survey on applications of deep learning in microscopy image analysis.
TL;DR: In this article, a review article introduces the applications of deep learning algorithms in microscopy image analysis, which include image classification, region segmentation, object tracking and super-resolution reconstruction, and discuss the drawbacks of existing deep learning-based methods, especially on the challenges of training datasets acquisition and evaluation, and propose the potential solutions.
Journal ArticleDOI
Imaging Observations of Asteroids with Hubble Space Telescope
Alex D. Storrs,Ben Weiss,B. Zellner,Win Burleson,Rukmini Sichitiu,Eddie Wells,Charles Kowal,David J. Tholen +7 more
TL;DR: The results of two Hubble Space Telescope (HST) observing programs, consisting of 11 imaging observations of 10 asteroids, were presented in this paper, where the primary focus of the projects was to search for faint companions (satellites) of these asteroids.
References
More filters
Book
Modern probability theory and its applications
TL;DR: Probability Theory as the study of Mathematical Models of Random Phenomena as mentioned in this paper is a generalization of probability theory for the study and analysis of statistical models of random variables.
Journal ArticleDOI
Image Evaluation and Restoration
TL;DR: The extent to which the processing approaches the optimum can be evaluated by determining the fraction of the total information content of the image which can be visually extracted after processing.
Journal ArticleDOI
Restoration of Turbulence-Degraded Images*
TL;DR: In this paper, the amplitude and phase coefficients of the two-dimensional Fourier series representing the degraded images were corrected by applying corrections to the optical transfer function of the turbulence measured at the time the images were photographed.