14116036
Measuring blocking artifacts using edge direction information
Block-based transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring blocking artifacts in images and videos. Instead of using the traditional pixel discontinuity along the block boundary, we use the edge directional information of the images. The new algorithm does not need the exact location of the block boundary thus is invariant to the displacement, rotation and scaling of the images. Experiments on various still images and videos show that the new blockiness measure is very efficient in terms of computational complexity and memory usage, and can produce blocking artifacts measurement consistent with subjective rating.
11110859
A locally-adaptive algorithm for measuring blocking artifacts in images and videos
Block transform coding is the most popular approach for image and video compression. The objective measurement of blocking artifacts plays an important role in the design, optimization, and assessment of image and video coding systems. This paper presents a new algorithm for measuring blocking artifacts in images and videos. It exhibits unique and useful features: 1) it examines the blocks individually so that it can measure the severity of blocking artifacts locally; 2) it is a one-pass algorithm in the sense that the image needs to be accessed only once; 3) it takes into account the blocking artifacts for high bit rate images and the flatness for the very low bit rate images; 4) the blocking artifacts measure is well-defined in the range of 0-10. Experiments on various still images and videos show that this blockiness measure is very efficient in terms of computational complexity and memory usage, and can produce consistent blocking artifacts measurement.
8588212
Temporal Aggregates in OWL-Time
In this paper, we describe our approach for representing temporal aggregates in OWL-Time, and a systematic way of mapping iCalendar recurrence sets to OWL-Time temporal sequences. We present several examples of natural language expressions for temporal aggregates and how they would be represented in OWL-Time; some examples can be described in both iCalendar and OWL-Time, while others can only be represented in OWL-Time. We also illustrate how we can translate from a natural language sentence to our representation.
39269573
An adaptive edge-preserving artifacts removal filter for video post-processing
We propose an adaptive edge-preserving artifacts removal filter (EPARF) for post-processing video compressed using block-based motion compensation so as to improve visual quality. The proposed filter is based on half-quadratic regularization, and it can adaptively remove both blocking and ringing artifacts while preserving object edges. The proposed algorithm has been applied to video sequences compressed by the MSRA scalable video coding (SVC) codec with block-based motion-compensated temporal filtering (MCTF). Experimental results demonstrate that EPARF can significantly improve both subjective and objective quality.
9260921
Complexity adaptive quantization for intra-frames in very low bit rate video coding
Conventional rate control schemes focus on the problem of finding an optimal quantization value for P- and B-frames. No rate control is available for the encoding of I-frames. This could pose big problems due to the large number of bits an I-frame could generate, and due to the fact that the number of bits varies drastically from sequence to sequence, depending on their image complexity. This problem becomes severe especially at very low bit rate. Therefore, a mechanism to allocate data bits to an I-frame according to its complexity is indispensable in order to have constant coding quality. This work presents a mechanism to establish for I-frames a generic relationship between the quantization value, data bits, and their image complexity. Experimental results show that this generic relationship provides a fairly accurate estimation of quantization value for an I-frame at given data bits and image complexity, and is very useful in controlling the data bits generated by an I-frame.
981043
Learning Event Durations from Event Descriptions
We have constructed a corpus of news articles in which events are annotated for estimated bounds on their duration. Here we describe a method for measuring inter-annotator agreement for these event duration distributions. We then show that machine learning techniques applied to this data yield coarse-grained event duration information, considerably outperforming a baseline and approaching human performance.
10609537
A new set of moment invariants for handwritten numeral recognition
In this paper, a new set of aspect invariant moments for handwritten numeral recognition are presented. These new moments exhibit two useful properties. Firstly, they are aspect invariant. This eliminates the need for size normalization of the unconstrained numerals. Secondly, their dynamic range remains constant with moment order. This overcomes the problem of diminishing high order moments, which occurs when other moment invariants are used. Thus, aspect invariant moments are particularly suitable for use with neural networks. Experimental results (using a multilayer perceptron and the backpropagation learning rule) show that a very high recognition rate (98.73%) and low substitution rate (1.06%) can be achieved on a totally unconstrained handwritten numeral database.<<ETX>>
6871628
REDUS: finding reducible subspaces in high dimensional data
Finding latent patterns in high dimensional data is an important research problem with numerous applications. The most well known approaches for high dimensional data analysis are feature selection and dimensionality reduction. Being widely used in many applications, these methods aim to capture global patterns and are typically performed in the full feature space. In many emerging applications, however, scientists are interested in the local latent patterns held by feature subspaces, which may be invisible via any global transformation.
 In this paper, we investigate the problem of finding strong linear and nonlinear correlations hidden in feature subspaces of high dimensional data. We formalize this problem as identifying reducible subspaces in the full dimensional space. Intuitively, a reducible subspace is a feature subspace whose intrinsic dimensionality is smaller than the number of features. We present an effective algorithm, REDUS, for finding the reducible subspaces. Two key components of our algorithm are finding the overall reducible subspace, and uncovering the individual reducible subspaces from the overall reducible subspace. A broad experimental evaluation demonstrates the effectiveness of our algorithm.
765245
CARE: Finding Local Linear Correlations in High Dimensional Data
Finding latent patterns in high dimensional data is an important research problem with numerous applications. Existing approaches can be summarized into 3 categories: feature selection, feature transformation (or feature projection) and projected clustering. Being widely used in many applications, these methods aim to capture global patterns and are typically performed in the full feature space. In many emerging biomedical applications, however, scientists are interested in the local latent patterns held by feature subsets, which may be invisible via any global transformation. In this paper, we investigate the problem of finding local linear correlations in high dimensional data. Our goal is to find the latent pattern structures that may exist only in some subspaces. We formalize this problem as finding strongly correlated feature subsets which are supported by a large portion of the data points. Due to the combinatorial nature of the problem and lack of monotonicity of the correlation measurement, it is prohibitively expensive to exhaustively explore the whole search space. In our algorithm, CARE, we utilize spectrum properties and effective heuristic to prune the search space. Extensive experimental results show that our approach is effective in finding local linear correlations that may not be identified by existing methods.
3409646
A survey of passive technology for digital image forensics
Over the past years, digital images have been widely used in the Internet and other applications. Whilst image processing techniques are developing at a rapid speed, tampering with digital images without leaving any obvious traces becomes easier and easier. This may give rise to some problems such as image authentication. A new passive technology for image forensics has evolved quickly during the last few years. Unlike the signature-based or watermark-based methods, the new technology does not need any signature generated or watermark embedded in advance. It assumes that different imaging devices or processing would introduce different inherent patterns into the output images. These underlying patterns are consistent in the original untampered images and would be altered after some kind of manipulations. Thus, they can be used as evidence for image source identification and alteration detection. In this paper, we will discuss this new forensics technology and give an overview of the prior literatures. Some concluding remarks are made about the state of the art and the challenges in this novel technology.
24069960
Study of Improved Hierarchy Genetic Algorithm Based on Adaptive Niches
Canonical genetic algorithms have the defects of pre-maturity and stagnation when applied in optimizing problems. In order to avoid the shortcomings, an adaptive niche hierarchy genetic algorithm (ANHGA) is proposed. The algorithm is based on the adaptive mutation operator and crossover operator to adjust the crossover rate and probability of mutation of each individual, whose mutation values are decided using individual gradient. This approach is applied in Percy and Shubert function optimization. Comparisons of niche genetic algorithm (NGA), hierarchy genetic algorithm (HGA) and ANHGA have been done by establishing a simulation model and the results of mathematics model and actual industrial model show that ANHGA is feasible and efficient in the design of multi-extremum.