A Continuous Probabilistic Framework for Image Matching
نویسندگان
چکیده
منابع مشابه
A Continuous Probabilistic Framework for Image Matching
In this paper we describe a probabilistic image matching scheme in which the im age representation is continuous and the similarity measure and distance computation are also de ned in the continuous domain Each image is rst represented as a Gaus sian mixture distribution and images are compared and matched via a probabilistic measure of similarity between distributions A common probabilistic an...
متن کاملA New Shearlet Framework for Image Denoising
Traditional noise removal methods like Non-Local Means create spurious boundaries inside regular zones. Visushrink removes too many coefficients and yields recovered images that are overly smoothed. In Bayesshrink method, sharp features are preserved. However, PSNR (Peak Signal-to-Noise Ratio) is considerably low. BLS-GSM generates some discontinuous information during the course of denoising a...
متن کاملA framework for ontologically-grounded probabilistic matching
In all scientific disciplines there are multiple competing and complementary theories that have been, and are being, developed. There are also observational data about which the theories can potentially make predictions. To enable semantic inter-operation between the data and the theories, we need ontologies to define the vocabulary used in them. For example, in the domain of minerals explorati...
متن کاملA Probabilistic-Logical Framework for Ontology Matching
Ontology matching is the problem of determining correspondences between concepts, properties, and individuals of different heterogeneous ontologies. With this paper we present a novel probabilistic-logical framework for ontology matching based on Markov logic. We define the syntax and semantics and provide a formalization of the ontology matching problem within the framework. The approach has s...
متن کاملA Probabilistic Framework for Matching Music Representations
In this paper we introduce a probabilistic framework for matching different music representations (score, MIDI, audio) by incorporating models of how one musical representation might be rendered from another. We propose a dynamical hidden Markov model for the score pointer as a prior, and two observation models, the first based on matching spectrogram data to a trained template, the second dete...
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: Computer Vision and Image Understanding
سال: 2001
ISSN: 1077-3142
DOI: 10.1006/cviu.2001.0946