A Bayesian segmentation methodology for parametric image models
نویسندگان
چکیده
منابع مشابه
A Bayesian Segmentation Methodology for Parametric Image Models
Region-based image segmentation methods require some criterion for determining when to merge regions. This paper presents a novel approach by introducing a Bayesian probability of homogeneity in a general statistical context. Our approach does not require parameter estimation , and is therefore particularly beneecial for cases in which estimation-based methods are most prone to error: when litt...
متن کاملA Bayesian Contour Measure for Image Segmentation
The Bayesian approach to image segmentation defines a penalty function of image partitions such that the function’s minima correspond to perceptually salient segments. We extend previous approaches following this framework by requiring that our image model sharply decrease in probability as a segment’s boundary is perturbed from its true position. Instead of making segment boundaries prefer ima...
متن کاملParametric Distributional Clustering for Image Segmentation
Unsupervised Image Segmentation is one of the central issues in Computer Vision. From the viewpoint of exploratory data analysis, segmentation can be formulated as a clustering problem in which pixels or small image patches are grouped together based on local feature information. In this contribution, parametrical distributional clustering (PDC) is presented as a novel approach to image segment...
متن کاملA Bayesian approach for image denoising in MRI
Magnetic Resonance Imaging (MRI) is a notable medical imaging technique that is based on Nuclear Magnetic Resonance (NMR). MRI is a safe imaging method with high contrast between soft tissues, which made it the most popular imaging technique in clinical applications. MR Imagechr('39')s visual quality plays a vital role in medical diagnostics that can be severely corrupted by existing noise duri...
متن کاملUnsupervised Bayesian image segmentation using wavelet-domain hidden Markov models
In this paper, we study unsupervised image segmentation using wavelet-domain hidden Markov models (HMMs). We first review recent supervised Bayesian image segmentation algorithms using wavelet-domain HMMs. Then, a new unsupervised segmentation approach is developed by capturing the likelihood disparity of different texture features with respect to wavelet-domain HMMs. The K-mean clustering is u...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Transactions on Pattern Analysis and Machine Intelligence
سال: 1995
ISSN: 0162-8828
DOI: 10.1109/34.368166