16586772
A new state-space approach for super-resolution image sequence reconstruction
Super-resolution imaging is to overcome the inherent limitations of image acquisition to create high-resolution images from their low-resolution counterparts. In this paper, a novel state-space approach is proposed to incorporate the temporal correlations among the low-resolution observations into the framework of the Kalman filtering. The proposed approach exploits both the temporal correlations information among the high-resolution images and the temporal correlations information among the low-resolution images to improve the quality of the reconstructed high-resolution sequence. Experimental results show that the proposed framework is superior to bi-linear interpolation, bi-cubic spline interpolation and the conventional Kalman filter approach, due to the consideration of the temporal correlations among the low-resolution images.
16178189
Super-resolution Imaging Using Grid Computing
The super-resolution (SR) imaging is to overcome the inherent limitations of the image acquisition systems to produce high-resolution images from their low-resolution counterparts. In our recent work, the Markov chain Monte Carlo (MCMC) technique has been successfully developed and shown as a promising stochastic approach for addressing the SR problem. However, the MCMC SR approach requires substantial amounts of computational resources, for it not only needs to generate a huge number of samples, but also requires an exhaustive search for obtaining an optimal prior image model. To tackle the above computation challenge, Grid computing is introduced for tackling the SR problem in this paper. The computationally- intensive MCMC SR task is broke down into a set of independent and small sub-tasks, which are further distributed and implemented in the grid computing environment. Their respective results are finally assembled to produce a high-resolution image as the final result of the entire MCMC SR task. Experiments are conducted to show that grid computing can effectively accelerating the execution time of the MCMC SR algorithm.
35577154
Tool support for software measurement, analysis and improvement
This paper presents our strategy, implementation, and experience with tool support for software measurement, analysis, and quality improvement in a commercial software development environment. The activities that need to be supported include: 1) gathering software product and process measurements, 2) analyzing measurement data, and 3) using the results to assess and improve software quality. We employed existing internal tools, commercial off-the-shelf tools, and new tools that we developed to gather and analyze data, and presented results. These tools were tailored to fit the application environments and were integrated through common rules, multiple purpose tools, and utility programs. This approach has been used successfully in supporting software measurement and quality improvement for several large commercial software products developed in the IBM Software Solutions Toronto Laboratory.
14734990
Reversible data-embedding with a hierarchical structure
Reversible data-embedding embeds data into a digital content (such as digital image, audio or video) such that an authorized party could decode the embedded data and completely restore the original content. In this paper, we present a hierarchically structured, multi-layer algorithm for digital images. Its basic component is an invertible sharpen filter called the difference expansion. The embedding capacity of this algorithm is substantially higher than results reported in previous reversible data-embedding algorithms. The visual quality of images after data-embedding is also among the best in the literature.
30955109
Web Testing for Reliability Improvement
In this chapter, we characterize problems for web applications, examine existing testing techniques that are potentially applicable to the web environment, and introduce a strategy for web testing aimed at improving web software reliability by reducing web problems closely identified with web source contents and navigations. Using information about web accesses and related failures extracted from existing web server logs, we build testing models that focus on the high-usage, high-leverage subsets of web pages for effective problem detection and reliability improvement. Related data are also used to evaluate web site operational reliability in providing the requested pages as well as the potential for reliability growth under effective testing. Case studies applying this approach to the web sites www.seas.smu.edu and www.kde.org are included to demonstrate its viability and effectiveness. We also outline extensions to our approach to address testing, defect analysis, and reliability improvement issues for the constantly evolving web as a whole by analyzing the dynamic web contents and other information sources not covered in our current case studies.
206622046
Fingerprint Alignment Using Similarity Histogram
The performance of fingerprint matching algorithm relies heavily on the accuracy of fingerprint alignment. Falsely aligning two feature sets extracted from two finger images of a fingerprint will increase the false rejection rate (FRR). In order to improve the performance of fingerprint matching algorithm, we present a new fingerprint alignment algorithm called similarity histogram approach (SHA). First, we calculate the local similarity matrix based on minutiae and associate ridges between two fingerprints. Then, similarity histograms of transformation parameters are constructed from local similarity matrix. In the end, the optimal transformation parameters are obtained using a statistical method. Experimental results on FVC databases show that our method is effective and reliable.
7621899
Test workload measurement and reliability analysis for large commercial software systems
This paper characterizes the testing environment for large commercial software systems, matches reliability model assumptions with the application environment, examines alternative test workload measurements that capture software usage information during testing, and uses two such measurements, test runs and transactions, as our usage dependent time measurements in reliability modeling. Our previous research using test runs, execution time, and test input information for reliability analysis and improvement is extended to ensure better test workload measurements for reliability assessment and prediction. This paper also identifies conditions under which different test workload measurements are appropriate, and presents reliability modeling results using these measurements in several products developed in the IBM Software Solutions Toronto Laboratory.