120935286
Automatic hyperparameter estimation in probabilistic image restoration algorithm based on Gibbs microcanonical distribution
For an original image given as an 8-gray-level image, the framework for image restoration is composed of Bayes statistics for the a priori probability distribution based on the microcanonical distribution. In this process, the a priori probability distribution serving as the microcanonical distribution is formulated on the basis of the variables characterizing the spatial flatness and smoothness of the image in terms of the number of nearest pixel pairs with different gray levels and the number of nearest pixel pairs with gray levels differing by 1. In the present paper, we propose a new method of estimation, from a degraded image, of the number of nearest pixel pairs with different gray levels and the number of nearest pixel pairs with gray levels differing by 1 in the original image. Then, based on that formulation, an iterative computation algorithm for the restoration of a 256-gray-level image is presented from the viewpoint of statistical mechanics. Through some numerical experiments, we investigate how the proposed method can improve the quality of the restored image. © 2004 Wiley Periodicals, Inc. Syst Comp Jpn, 36(1): 68–78, 2005; Published online in Wiley InterScience (). DOI 10.1002sscj.10365
2198276
Coupled Markov random field models with phases as line field and region field
We investigate a boundary-based and a region-based coupled Markov random field model, both of which are useful in image restorations of gray-level images. In the conventional boundary-based and the conventional region-based coupled Markov random field models, both a line field and a region field take only two discrete states, 0 and 1. In the boundary-based coupled random field model, existence and nonexistence of the edge at each nearest-neighbor pair of pixels are denoted by 1 and 0, respectively. In the region-based coupled random field model, some different regions at each pixel are labeled by discrete numbers. We propose a boundary-based coupled Markov random field model with continuous line field and a region-based coupled Markov random field model with continuous segmentation field from a standpoint of a plane rotator model in statistical mechanics. The iterative algorithms for image restoration are constructed by using a mean-field approximation. We investigate how the proposed models produce a better quality of restored images. © 2003 Wiley Periodicals, Inc. Syst Comp Jpn, 34(7): 24–33, 2003; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/scj.10364
20447387
Cluster ZTP in the recovery of an image
Abstract Cluster ZTP (zero-temperature process) is proposed as a method of image recovery and examined for 8-valued images. The cluster ZTP is an iterative algorithm for the search of an approximately optimal solution of an energy minimization problem.
119404260
Probabilistic image processing based on the Q-Ising model by means of the mean-field method and loopy belief propagation
The framework is presented of Bayesian image restoration for multi-valued images by means of the Q-Ising model. Hyper parameters in the probabilistic model are determined so as to maximize the marginal likelihood. Practical algorithms are described based the conventional mean-field approximation and loopy belief propagation. We compare the results empirically with those provided by conventional filters and the new methods are found to be superior.
11983347
Linear Response Formula in Generalized Belief Propagation for Probabilistic Inference
Linear response formulas for the generalized belief propagation in approximate inference are derived by using generalized belief propagation. The linear response formulas can give us the marginal probability between every pair of nodes and we obtain good accuracy in some examples of practical probabilistic inferences
7133208
Statistical Learning Procedure in Loopy Belief Propagation for Probabilistic Image Processing
We give a fast and practical algorithm for statistical learning hyperparameters from observable data in probabilistic image processing, which is based on Gaussian graphical model and maximum likelihood estimation. Although hyperparameters in the probabilistic model are determined so as to maximize a marginal likelihood, a practical algorithm is described for the EM algorithm with the loopy belief propagation which is one of approximate inference algorithms in artificial intelligence
15731243
TORNADO: omnistereo video imaging with rotating optics
One of the key techniques for vision-based communication is omnidirectional stereo (omnistereo) imaging, in which stereoscopic images for an arbitrary horizontal direction are captured and presented according to the viewing direction of the observer. Although omnistereo models have been surveyed in several studies, few omnistereo sensors have actually been implemented. In this paper, a practical method for capturing omnistereo video sequences using rotating optics is proposed and evaluated. The rotating optics system consists of prism sheets, circular or linear polarizing films, and a hyperboloidal mirror. This system has two different modes of operation with regard to the separation of images for the left and right eyes. In the high-speed shutter mode, images are separated using postimage processing, while, in the low-speed shutter mode, the image separation is completed by optics. By capturing actual images, we confirmed the effectiveness of the methods.
34835412
A Relational Data Language with Simplified Binary Relation Handling Capability
In order to develop a general purpose research information system, we have introduced a new relational data language RLB (Relational data Language with simplified Binary relation handling capability), which can handle bibliographic data as well as data handled by ordinary data base systems. RLB is based on relational calculus introduced by Codd, but allows queries to be written in relatively high level expressions by defining and using proper binary relations over a set of n-ary relations. The characteristics of this language are as follows: (1) Binary relations between attributes or compound attributes can be defined and used to formulate queries; (2) Familiar operations for binary relations such as a concatenation, a closure operation, Boolean operations and comparison operators are provided to simplify queries; (3) Binary relations are classified into several types by their corresponding graphs. This classification can be used for checking storage operations such as updating, insertion and deletion, as well as for selecting efficient physical storage structures; (4) Dependencies between attributes are also regarded as binary relations and thus, they are classified for the same objectives described in (3). In this classification, functional dependencies, multivalued dependencies and set - set dependencies are contained; (5) It can provide several facilities similar to mapping oriented languages (for example, SEQUEL) or network model based languages (for example, LSL). Furthermore, an output system for binary relations between domain compatible attributes is also described, which produces a tree expansion of the given graph.
28024409
The Concept of Memory-Based Thread Execution by Highly Functional Memory Controller
18847598
A method for panoramic stereo image acquisition
One of the key technologies for one-to-many visual communication is panoramic stereo, in which stereoscopic images for arbitrary horizontal directions are presented to multiple users, according to their positions and postures. In this paper, one of the methods for capturing panoramic stereo motion pictures is proposed and evaluated, along with an experimentation. Through preliminary experimentation, we have confirmed the effectiveness of methods using a curved mirror.
1810071
Testing of Join Dependency Preserving by a Modified Chase Method