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Importance sampling (IS) is a change-of-measure technique for speeding up the simulation of rare events in stochastic systems. In this paper, we presented an approach uses Importance Sampling technique for efficient estimation of software reliability via Markov software usage models in statistical testing. By suitable changes of the probabilities of state transitions during test, an iterative method based on the Ali-Silvey distance is proposed for this choice, and an unbiased reliability estimator with zero variance is obtained. A learning algorithm for the computation of optimal transition probabilities of the Markov chain usage model is also presented and experimental results of this algorithm are reported.

Combinatorial interaction testing (CIT) is a method to detect the fault interactions among the parameters or components in a system. However the most works in the field of combinatorial interaction testing focus on detecting interaction faults rather than locating them. (d, t)-locating arrays and (d, t)-detecting arrays were proposed by C. J. Colbourn and D. W. McClary to locate and detect the interaction fault. In the paper, we study the structure of the special fault locating array that is able to locate sole interaction fault among the parameters or components, namely (1, t)-detecting arrays, and then propose the concept and construction method of approximate error locating array based on the special error locating array. The AETG-like algorithms to generate these special arrays are provided.

Perceptual quality measurement of three-dimensional (3D) visual signals has become a fundamental challenge in 3D imaging fields. This paper proposes a novel no-reference (NR) 3D visual quality measurement (VQM) metric that uses simulations of the primary visual cortex (V1) of binocular vision. As the major technical contribution of this study, perceptual properties of simple and complex cells are considered for NR 3D-VQM. More specifically, the metric simulates the receptive fields of simple cells (one class of V1 neurons) using Gaussian derivative functions, and the receptive fields of complex cells (the other class of V1 neurons) using disparity energy responses and binocular rivalry responses. Subsequently, various quality-aware features are extracted from the primary visual cortex; these will change in the presence of distortions. Finally, those features are mapped to the subjective quality score of the distorted 3D visual signal by using support vector regression (SVR). Experiments on two publicly available 3D databases confirm the effectiveness of our proposed metric, compared to the relevant full-reference (FR) and NR metrics.

Perceptual no-reference (NR) quality measurement of stereoscopic images has become a challenging issue in three-dimensional (3D) imaging fields. In this article, we propose an efficient binocular quality-aware features extraction scheme, namely generalized local ternary patterns (GLTP) of binocular energy response, for general-purpose NR stereoscopic image quality measurement (SIQM). More specifically, we first construct the binocular energy response of a distorted stereoscopic image with different stimuli of amplitude and phase shifts. Then, the binocular quality-aware features are generated from the GLTP of the binocular energy response. Finally, these features are mapped to the subjective quality score of the distorted stereoscopic image by using support vector regression. Experiments on two publicly available 3D databases confirm the effectiveness of the proposed metric compared with the state-of-the-art full reference and NR metrics.

Three-dimensional (3D) technology has become immensely popular in recent years and widely adopted in various applications. Hence, perceptual quality measurement of symmetrically and asymmetrically distorted 3D images has become an important, fundamental, and challenging issue in 3D imaging research. In this paper, we propose a binocular-vision-based 3D image-quality measurement (IQM) metric. Consideration of the 3D perceptual properties of the primary visual cortex (V1) and the higher visual areas (V2) for 3D-IQM is the major technical contribution to this research. To be more specific, first, the metric simulates the receptive fields of complex cells (V1) using binocular energy response and binocular rivalry response and the higher visual areas (V2) using local binary patterns features. Then, three similarity scores of 3D perceptual properties between the reference and distorted 3D images are measured. Finally, by using support vector regression, three similarity scores are integrated into an overall 3D quality score. Experimental results for two public benchmark databases demonstrate that, in comparison with most current 2D and 3D metrics, the proposed metric achieves significantly higher consistency in alignment with subjective fidelity ratings.

We propose a new watermarking algorithm for stereoscopic image tamper detection and self-recovery in three-dimensional multimedia services. Initially, left and right views of stereoscopic image are divided into nonoverlapping 2×2 blocks in order to improve the accuracy of tamper localization in an image. As the left and right views of a stereoscopic image are not independent from each other but have an inter-view relationship, every block of a stereoscopic image is classified into matching block or nonmatching block and then block disparities are obtained. Both matching blocks in the left and right views have similar pixel values, so that fewer bits are allocated for recovery watermark generation, which can increase the quality of watermarked stereoscopic images. A hierarchical tamper-detection strategy with a four-level checkup is presented to improve the accuracy of tamper localization. Additionally, two copies of block (matching block and nonmatching block) information are embedded into the stereoscopic image, and it assures the quality of tampered recovery. For the nonmatching block recovery, two copies of the partner block are embedded into their chaotic mapping blocks, which supply the second chance for tamper recovery. For the matching block recovery, the inter-view relationship between tampers of left and right views supplies the third chance for tamper recovery. Experimental results show that the proposed algorithm can not only detect and locate tampers in stereoscopic image more accurately but also recover the tampered regions better, compared with other algorithms.