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A new automatic compression scheme that adapts to any image set is presented in this thesis. The proposed scheme requires no a priori knowledge on the properties of the image set. This scheme is obtained using a unified graph-theoretical framework that allows for compression strategies to be compared both theoretically and experimentally. This strategy… (More)

- Barry Gergel, Howard Cheng, Clinton Nielsen, Xiaobo Li
- IPCV
- 2006

While the compression of individual images have been studied extensively, there have been fewer studies on the problem of compressing image sets. A number of schemes have been proposed to compress an image set by taking advantage of the inter-image redundancy between pairs of images. In this paper, we present a unified graph-theoretic framework that… (More)

- Barry Gergel, Howard Cheng, Xiaobo Li
- Data Compression Conference (DCC'06)
- 2006

Summary form only given. This paper presents a framework to effectively compress sets of images in a lossless manner. An image set is represented as a graph and its minimum spanning tree is computed to decide which images and differences to encode. The Centroid scheme and the previous MST scheme can both be represented as a spanning tree in our graph. Thus,… (More)

- Michael Smit, Barry Gergel, H. James Hoover, Eleni Stroulia
- 2011 27th IEEE International Conference on…
- 2011

Maintainability is a desired property of software, and a variety of metrics have been proposed for measuring it, focusing on different notions of complexity and code readability. Many practices have been proposed to improve maintainability through code refactorings: improving the cohesion, simplification of interfaces, renamings to improve… (More)

- Barry Gergel, Anthony Schmieder, Xiaobo Li, Howard Cheng
- IPCV
- 2008

The automatic compression strategy proposed by Gergel et al. is a near-optimal lossy compression scheme for a given collection of images whose interimage relationships are unknown. Their algorithm uses the root mean square error (RMSE) as a measure of the similarity between two images, in order to predict the compressibility of the difference image. Gergel… (More)

- Howard Cheng, Barry Gergel, Ethan Kim, Eugene V. Zima
- ACM SIGSAM Bulletin
- 2005

We consider the evaluation of the truncated hypergeometricseries
[EQUATION]
to high precision, where <i>a, b, p</i>, and<i>q</i> are polynomials with integer coefficients,… (More)

- Anthony Schmieder, Howard Cheng, Barry Gergel, Xiaobo Li
- IPCV
- 2008

A number of minimum spanning tree algorithms have been proposed for lossy compression of image sets. In these algorithms, a complete graph is constructed from the entire image set and possibly an average image, and a minimum spanning tree is used to determine which difference images to encode. In this paper, we propose a hierarchical minimum spanning tree… (More)

- B. Gergel
- 2005

Interest in quantum computing, nanotechnology, and low power consumption circuits is fueling the expanding research in reversible logic synthesis. A reversible function is one that generates a unique output vector for every input vector. Traditional circuits are designed with AND and OR gates that allow fan-outs and loop back results which often results in… (More)

- SEBASTIAN HANLON, Stephen Wismath, +7 authors Barry Gergel
- 2006

The GLuskap system for interactive three-dimensional graph drawing applies techniques of scientific visualization and interactive systems to the construction, display, and analysis of graph drawings. Important features of the system include support for large-screen stereographic 3D display with immersive head-tracking and motion-tracked interactive 3D wand… (More)

- Howard Cheng, Barry Gergel, +4 authors ETHAN KIM

Hypergeometric series are used to approximate many important constants, such as e and Apéry’s constant ζ(3). The evaluation of such series to high precision has traditionally been done by binary splitting followed by integer division. However, the numerator and the denominator computed by binary splitting usually contain a very large common factor. In this… (More)