33123759
Assessment of Color Video Quality Based on Quaternion Singular Value Decomposition
Measurement of visual quality is of fundamental importance for numerous video processing applications. In this paper, we proposed a full-reference color video quality assessment based on quaternion singular value decomposition(QSVD), which takes into account the luminance, chrominance and gradient information of each pixel and treats them as a whole. The algorithm is tested on the video quality experts group (VQEG) Phase I FR-TV test dataset. Experiments show that it has good correlation with perceived video quality.
23645569
Geometric Analysis of Particle Motion in a Vector Image Field
This paper proposes a geometrical model for the Particle Motion in a Vector Image Field (PMVIF) method. The model introduces a c-evolute to approximate the edge curve in the gray-level image. The c-evolute concept has three major novelties: (1) The locus of Particle Motion in a Vector Image Field (PMVIF) is a c-evolute of image edge curve; (2) A geometrical interpretation is given to the setting of the parameters for the method based on the PMVIF; (3) The gap between the image edge’s critical property and the particle motion equations appeared in PMVIF is padded. Our experimental simulation based on the image gradient field is simple in computing and robust, and can perform well even in situations where high curvature exists.
7606399
A fuzzy image metric with application to fractal coding
Image quality assessment is an important issue addressed in various image processing applications such as image/video compression and image reconstruction. The peak signal-to-noise ratio (PSNR) with the L(2)-metric is commonly used in objective image quality assessment. However, the measure does not agree very well with the human visual perception in many cases. A fuzzy image metric (FIM) is defined based on Sugeno's (1977) fuzzy integral. This new objective image metric, which is to some extent a proper evaluation from the viewpoint of the judgment procedure, is closely approximates the subjective mean opinion score (MOS) with a correlation coefficient of about 0.94, as compared to 0.82 obtained using the PSNR. Compared to the L(2)-metric, we demonstrate that a better performance can be achieved in fractal coding by using the proposed FIM.
37994970
Image coding quality assessment using fuzzy integrals with a three-component image model
Based on importance measures and fuzzy integrals, a new assessment method for image coding quality is presented in this paper. The proposed assessment is based on two subevaluations. In the first subevaluation, errors on edges, textures, and flat regions are computed individually. The errors are then assessed using an assessment function. A global evaluation with Sugeno fuzzy integral is then obtained based on the importance measure of edge, texture, and flat region. In the second subevaluation, an importance measure is first established depending on the types of regions where errors occur, a subtle evaluation is then obtained using Sugeno fuzzy integral on all pixels of the image. A final evaluation is obtained based on the two subevaluations. Experimental results show that this new image quality assessment closely approximates human subjective tests such as mean opinion score with a high correlation coefficient of 0.963, which is a significant improvement over peak signal-to-noise ratio, picture quality scale, and weighted mean square error, three other image coding quality assessment methods, which have the correlation coefficients of 0.821, 0.875, and 0.716, respectively.
31400188
Image Recovery from Broken Image Streams
This paper presents an approach for image recovery from broken image streams based on an image continuity model. The information to be recovered includes the header of an image (width, height, color space etc.) and the data stream which might have been partially damaged. We begin our discussion on common image formats and necessary information for the image recovery. We then define several measures on image contents to facilitate the image recovery. Using these measures, an effective recovery algorithm is proposed. Experimental results show that the algorithm can successfully recover images of different formats, even multi-frame images from broken image streams in most cases.
295516
A fuzzy metric for image quality assessment
Image quality assessment is an important issue addressed in various image processing applications such as image/video compression and image reconstruction. The peak signal-to-noise ratio (PSNR) with the L/sup 2/-metric is commonly used in objective image quality assessment. However, the measure does not agree very well with human visual perception in many cases. In this paper, a fuzzy image metric (FIM) is defined based on M. Sugeno's (1974) fuzzy integral. This new objective image metric, which is to some extent a proper evaluation from the viewpoint of the judgement procedure, is closely approximates the subjective mean opinion score (MOS) with a correlation coefficient of about 0.94, as compared to 0.82 obtained using PSNR.
15133148
Modeling Image Data for Effective Indexing and Retrieval in Large General Image Databases
In this paper, we propose an image semantic model based on the knowledge and criteria in the field of linguistics and taxonomy. Our work bridges the "semantic gap" by seamlessly exploiting the synergy of both visual feature processing and semantic relevance computation in a new way, and provides improved query efficiency and effectiveness for large general image databases. Our main contributions are as follows: we design novel data structures, namely, a lexical hierarchy, an image-semantic hierarchy, and a number of atomic semantic domains, to capture the semantics and the features of the database, and to provide the indexing scheme. We present a novel image query algorithm based on the proposed structures. In addition, we propose a novel term expansion mechanism to improve the lexical processing. Our extensive experiments indicate that our proposed techniques are effective in achieving high runtime performance with improved retrieval accuracy. The experiments also show that the proposed method has good scalability.
17839950
Reorganizing global schedules for register allocation
Instruction scheduling is an important compiler technique for exploiting more instruction-level parallelism (ILP) in high-performance microprocessors, and in this paper, we study how to perform global instruction scheduling before register allocation (prepass scheduling) for control-intensive non-numerical applications. As the number of parallel function units in modern microprocessors has increased, compiler writers have increased the size of prepass scheduling regions and the number of speculative operations scheduled. However, if prepass scheduling is not carefully managed, it is easy to create places in a prepass schedule that require more register resources than are architecturally available. We propose an approach that maintains the effectiveness of prepass scheduling in exploiting ILP even with the constraint of a limited number of architectural registers. In particular, we show that the pairing of a greedy prepass scheduler with a code reorganizer performs significantly better than the common approach of using a single register-pressure-sensitive scheduler. Our experimental results show that our non-backtracking, codereorganizing algorithm can eliminate most of the excessive register pressure created by greedy ILP scheduling, and thus improve the overall performance of the globally scheduled regions.
34310397
Predictive Queries Algorithm Based on Probability Model over Data Streams
Mining the evolving trends of an online data stream and forecasting the data values in the future can provide important support for the decision-making in many time-sensitive applications. This paper models an online data stream as a continuous state transitions process by mapping the possibly infinite stream data into finite states, and uses state transition disGraph (STG) to maintain the track of the state transactions. By studying the statistic information of the history state transitions, the future values can be predicted based on the theory of Markov chain. Extensive simulation experiments are conducted and show that the predictive performance of our method is preferable to that of the existing analogous algorithms.
10592217
Design Wizards and Visual Programming Environments for GenVoca Generators
Domain-specific generators will increasingly rely on graphical languages for declarative specifications of target applications. Such languages will provide front-ends to generators and related tools to produce customized code on demand. Critical to the success of this approach will be domain-specific design wizards, tools that guide users in their selection of components for constructing particular applications. The authors present the P3 ContainerStore graphical language, its generator, and design wizard.
33357953
PISA: Federated Search in P2P Networks with Uncooperative Peers
Recently, federated search in P2P networks has received much attention. Most of the previous work assumed a cooperative environment where each peer can actively participate in information publishing and distributed document indexing. However, little work has addressed the problem of incorporating uncooperative peers, which do not publish their own corpus statistics, into a network. This paper presents a P2P-based federated search framework called PISA which incorporates uncooperative peers as well as the normal ones. In order to address the indexing needs for uncooperative peers, we propose a novel heuristic query-based sampling approach which can obtain high-quality resource descriptions from uncooperative peers at relatively low communication cost. We also propose an effective method called RISE to merge the results returned by uncooperative peers. Our experimental results indicate that PISA can provide quality search results, while utilizing the uncooperative peers at a low cost.