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Analysis of Variance in Statistical Image Processing
Ludwik Kurz,M. Hafed Benteftifa +1 more
TLDR
This paper presents a meta-analysis of statistical linear models used in image segmentation to derive Radial masks in line and edge detection and some approaches to image restoration.Abstract:
Preface 1. Introduction 2. Statistical linear models 3. Line detection 4. Edge detection 5. Object detection 6. Image segmentation 7. Radial masks in line and edge detection 8. Performance analysis 9. Some approaches to image restoration References Index.read more
Citations
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Journal ArticleDOI
On minimum variance thresholding
TL;DR: It turns out that the bias for the Otsu method is due to differences in class variances or class probabilities and the resulting threshold is biased towards the component with larger class variance or larger class probability.
Journal ArticleDOI
$t$ -Tests, $F$ -Tests and Otsu's Methods for Image Thresholding
Jing-Hao Xue,D. M. Titterington +1 more
TL;DR: It is naturally demonstrated that the extension of Otsu's binarization method to multi-level thresholding is equivalent to the search for optimal thresholds that provide the largest F -statistic through one-way analysis of variance (ANOVA).
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Robust edge detection in noisy images
TL;DR: A new edge detector based on the robust rank-order (RRO) test which is a useful alternative to Wilcoxon test, using rxr window for detecting edges of all possible orientations in noisy images, and appears to be the most robust to variations in noise.
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Subjective Assessment of Region of Interest-Aware Adaptive Multimedia Streaming Quality
TL;DR: The performance analysis of ROIAS is presented in terms of the impact on user perceived video quality measured using subjective video quality assessment techniques based on human subjects and the benefit of using ROIAS for adaptive video quality delivery is demonstrated.
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Robust edge detection
Zujun Hou,Zujun Hou,Tong San Koh +2 more
TL;DR: The results show that the performance of the proposed edge detector is stable and reliable under severe impulsive noise conditions.
References
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Journal ArticleDOI
Boundary detection by constrained optimization
TL;DR: A statistical framework is used for finding boundaries and for partitioning scenes into homogeneous regions and incorporates a measure of disparity between certain spatial features of block pairs of pixel gray levels, using the Kolmogorov-Smirnov nonparametric measures of difference between the distributions of these features.
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Structural Image Restoration through Deformable Templates
TL;DR: In this paper, a prior Gaussian distribution is given on the set of continuous mappings, and a posterior distribution is then obtained and has the form of a nonlinear perturbation of the Gaussian measure on the space of mappings.
Journal ArticleDOI
Stochastic geometry models in high-level vision
TL;DR: The use of Markov models from stochastic geometry as priors in ‘high-level’ computer vision is surveyed, in direct analogy with the use of discrete Markov random fields in ’low-level' vision.
Journal ArticleDOI
Split-and-merge image segmentation based on localized feature analysis and statistical tests
TL;DR: An adaptive split-and-merge image segmentation algorithm based on characteristic features and a hypothesis model is proposed and one of the key processes, the determination of region homogeneity, is treated as a sequence of decision problems in terms of predicates in the hypothesis model.
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