12486810
A new class of biorthogonal wavelet systems for image transform coding
We construct general biorthogonal Coifman wavelet systems, a new class of compactly supported biorthogonal wavelet systems with vanishing moments equally distributed for a scaling function and wavelet pair. A time-domain design method is employed and closed-form expressions for the impulse responses and the frequency responses of the corresponding dual filters are derived. The resulting filter coefficients are all dyadic fractions, which is an attractive feature in the realization of multiplication-free discrete wavelet transform. Even-ordered systems in this family are symmetric, which correspond to linear-phase dual filters. In particular, three filterbanks (FBs) in this family are systematically verified to have competitive compression potential to the 9-7 tap biorthogonal wavelet FB by Cohen et al., which is currently the most widely used one in the field of wavelet transform coding. In addition, the proposed FB's have much smaller computational complexity in terms of floating-point operations required in transformation, and therefore indicate a better tradeoff between compression performance and computational complexity.
25090129
Comments on "A translation- and scale-invariant adaptive wavelet transform"
Xiong et al. presented a translationand scale-invariant adaptive wavelet transform. We show that their renormalized signal (pre-wavelet transform) is already translation- and scale-invariant. Thus, it is not just invariant under the wavelet transform. We give a necessary and sufficient condition for renormalized signals to be affine transform invariant.
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.
6315327
Reversible data embedding using a difference expansion
Reversible data embedding has drawn lots of interest recently. Being reversible, the original digital content can be completely restored. We present a novel reversible data-embedding method for digital images. We explore the redundancy in digital images to achieve very high embedding capacity, and keep the distortion low.
18528442
Better Reliability Assessment and Prediction through Data Clustering
This paper presents a new approach to software reliability modeling by grouping data into clusters of homogeneous failure intensities. This series of data clusters associated with different time segments can be directly used as a piecewise linear model for reliability assessment and problem identification, which can produce meaningful results early in the testing process. The dual model fits traditional software reliability growth models (SRGMs) to these grouped data to provide long-term reliability assessments and predictions. These models were evaluated in the testing of two large software systems from IBM. Compared with existing SRGMs fitted to raw data, our models are generally more stable over time and produce more consistent and accurate reliability assessments and predictions.
39882874
A comparison of measurement and defect characteristics of new and legacy software systems
Abstract This paper compares the quality characteristics of a large legacy software system and a new one. Defect fixes applied to specific modules during testing are used as the direct quality metric. Indirect quality indicators used in this paper include software metrics of various product and process attributes, including design, size, change, and complexity. We analyze and compare the measurement results by examining their individual distributions, the correlations between defects and quality indicators, and tree-based models linking defects to quality indicators. In both these systems, most of the defects are found to be concentrated on relatively few high-defect modules, which points to the need for appropriate risk identification techniques so that defect removal effort can be focused on those high-defect modules for effective quality improvement. In addition, defects in the legacy system are more closely related to change and data complexity metrics; while defects in the new system are more closely related to various design metrics. These results demonstrate different measurement characteristics for these two types of software systems, and suggest that different quality analysis and improvement methods may be more appropriate and effective for different kinds of software systems.
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.
3252382
Quality-evaluation models and measurements
Quality can determine a software product's success or failure in today's competitive market. Among the many characteristics of quality, some aspects deal directly with the functional correctness or the conformance to specifications, while others deal with usability, portability, and so on. Correctness - that is, how well software conforms to requirements and specifications - is typically the most important aspect of quality, particularly when crucial operations depend on the software. Even for market segments in which new features and usability take priority, such as software for personal use in the mass market, correctness is still a fundamental part of the users' expectations. We compare and classify quality-evaluation models, particularly those evaluating the correctness aspect of quality, and examine their data requirements to provide practical guidance for selecting appropriate models and measurements.
37559798
Measurement and continuous improvement of software reliability throughout software life-cycle
Abstract Software reliability is one of the most important aspects of software quality. However, most of the existing techniques focus on the system testing and other late stages of development life-cycle. Therefore, they are not effective for early problem identification and reliability improvement. This paper describes our recent work in establishing predictive linkage between software reliability and other entities that we can measure and control early in the development cycle, and using such predictive relations to drive continuous reliability improvement.