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Recent advances in imaging technology have resulted in a proliferation of images across different media. Before it reaches the end user, these signals undergo several transformations, which may introduce defects/artifacts that affect the perceived image quality. In order to design and evaluate these imaging systems, perceived image quality must be measured. This work focuses on analysis of print image defects and characterization of printer artifacts such as banding and graininess by using a human visual system (HVS) based framework. Specifically the work addresses the prediction of visibility of print defects (banding and graininess) by representing the print defects in terms of the orthogonal wavelet and sinusoidal basis functions and combining the detection probabilities of each basis functions to predict the response of the human visual system (HVS). The detection probabilities for basis function components and the simulated print defects are obtained from separate subjective tests. The prediction performance from both the wavelet based and sine based approaches is compared with the subjective testing results.The wavelet based prediction performs better than the sinusoidal based approach and can be a useful technique in developing measures and methods for print quality evaluations based on HVS

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Supporting User-defined Granularities and Indeterminacy in a Spatiotemporal Conceptual Model Vijay Khatri and Sudha Ram and Richard T. Snodgrass, and Grady O'Brien April 5, 2001 TR-55

Granularities are integral to spatial and temporal data. A large number of applications require storage of facts along with their temporal and spatial context, which needs to be expressed in terms of appropriate granularities. For many real-world applications, a single granularity in the database is insufficient. In order to support any type of spatial or temporal reasoning, the semantics related to granularities needs to be embedded in the database. Specifying granularities related to facts is an important part of conceptual database design because underspecifying the granularity can restrict an application, affect the relative ordering of events, and impact the topological relationships. Closely related to granularities is indeterminacy, i.e., an occurrence time or location associated with a fact that is not known exactly. In this paper, we present an ontology for spatial granularities that is a natural analog of temporal granularities. We propose an upward-compatible, annotation-based spatiotemporal conceptual model that can comprehensively capture the semantics related to spatial and temporal granularities, and indeterminacy without requiring new spatiotemporal constructs. We specify the formal semantics of this spatiotemporal conceptual model via translation to a conventional conceptual model. To underscore the practical focus of our approach, we describe an on-going case study. We apply our approach to a hydrogeologic application at the United States Geologic Survey and demonstrate that our proposed granularitybased spatiotemporal conceptual model is straightforward to use and is comprehensive

Reconciling Point-based and Interval-based Semantics in Temporal Relational Databases: A Proper Treatment of the Telic/Atelic Distinction

The analysis of the semantics of temporal data and queries plays a central role in the area of temporal databases. Although many different algebr and models have been proposed, almost all of them are based on a point-based (snapshot) semantics for data. On the other hand, in the areas of linguistics, philosophy, and, recently, artificial intelligence, a debated issue concerns the use of an interval-based versus a point-based semantics. In this paper, we first show some problems inherent in the adoption of a point-based semantics for data, and argue that these problems arise because there is no distinction drawn in the data between telic and atelic facts. We then introduce a three-sorted temporal model and algebra which properly copes with these issues, and which achieves a great flexibility via the introduction of coercion functions for transforming relations of one sort into relations of the other at query time. We show that it is possible to extend SQL/Temporal in a minimal fashion to support this augmented algebra

On the Ontological Expressiveness of Temporal

It is widely recognized that temporal aspects of database schemas are prevalent, but also difficult to capture using the ER model. The database research community's response has been to develop temporally enhanced ER models. However, these models have not been subjected to systematic evaluation