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Found 18 papers, 4 papers with code
Fast Two-step Blind Optical Aberration Correction
The optics of any camera degrades the sharpness of photographs, which is a key visual quality criterion.
Investigating Neural Architectures by Synthetic Dataset Design
It is therefore impossible to know what cues a given neural structure is taking advantage of in such data.
Non-Semantic Evaluation of Image Forensics Tools: Methodology and Database
With the aim of evaluating image forensics tools, we propose a methodology to create forgeries traces, leaving intact the semantics of the image.
Robust Rational Polynomial Camera Modelling for SAR and Pushbroom Imaging
The Rational Polynomial Camera (RPC) model can be used to describe a variety of image acquisition systems in remote sensing, notably optical and Synthetic Aperture Radar (SAR) sensors.
Residual Learning for Effective joint Demosaicing-Denoising
Moreover, it is very difficult to change this order, because once the image is demosaicked, the statistical properties of the noise will be changed dramatically.
A Review of an Old Dilemma: Demosaicking First, or Denoising First?
In this paper, we review the main variants of these strategies and carry-out an extensive evaluation to find the best way to reconstruct full color images from a noisy mosaic.
Reducing Anomaly Detection in Images to Detection in Noise
Anomaly detectors address the difficult problem of detecting automatically exceptions in an arbitrary background image.
Non-Local Video Denoising by CNN
To the best of our knowledge, this is the first successful application of a CNN to video denoising.
Model-blind Video Denoising Via Frame-to-frame Training
Modeling the processing chain that has produced a video is a difficult reverse engineering task, even when the camera is available.
Quantitative Evaluation of Base and Detail Decomposition Filters Based on their Artifacts
For each of these artifacts we design a test-pattern and its attached measurement formula.
Image Anomalies: a Review and Synthesis of Detection Methods
We review the broad variety of methods that have been proposed for anomaly detection in images.
Psychophysics, Gestalts and Games
Using a computational quantitative version of the non-accidentalness principle, we raise the possibility that the psychophysical and the (older) gestaltist setups, both applicable on dot or Gabor patterns, find a useful complement in a Turing test.
A survey of exemplar-based texture synthesis
The two main approaches are statistics-based methods and patch re-arrangement methods.
Accurate Motion Estimation through Random Sample Aggregated Consensus
This yields RANSAAC, a framework that improves systematically over RANSAC and its state-of-the-art variants by statistically aggregating hypotheses.
From line segments to more organized Gestalts
In this paper, we reconsider the early computer vision bottom-up program, according to which higher level features (geometric structures) in an image could be built up recursively from elementary features by simple grouping principles coming from Gestalt theory.
An analysis of the factors affecting keypoint stability in scale-space
In practice, however, scale invariance may be weakened by various sources of error inherent to the SIFT implementation affecting the stability and accuracy of keypoint detection.
Comparing Feature Detectors: A bias in the repeatability criteria, and how to correct it
We apply this variant to revisit the popular benchmark by Mikolajczyk et al., on classic and new feature detectors.
Finding Vanishing Points via Point Alignments in Image Primal and Dual Domains
We present a novel method for automatic vanishing point detection based on primal and dual point alignment detection.
