35277097
Maximum-likelihood parameter estimation for image ringing-artifact removal
At low bit rates, image compression codecs based on overlapping transforms introduce spurious oscillations known as ringing artifacts in the vicinity of major edges. Unlike previous works, we present a maximum-likelihood approach to the ringing-artifact removal problem. Our approach employs a parameter estimation method based on the k-means algorithm with the number of clusters determined by a cluster-separation measure. The proposed algorithm and its simplified approximation are applied to JPEG2000 compressed images. Our results show effective and efficient removal of ringing artifacts.
2066487
Maximum likelihood parameter estimation for image ringing artifact removal
At low bit rates, image compression codecs based on overlapping transforms introduce spurious oscillation known as ringing artifacts in the vicinity of major edges. The image quality can be enhanced considerably by removing the artifacts. We present a maximum likelihood approach to the ringing artifact removal problem. Our approach employs a parameter estimation method based on the k-means algorithm with the number of clusters determined by a cluster separation measure. The proposed algorithm and its simplified approximation are applied to JPEG2000 compressed images to demonstrate their effectiveness.
16821874
Interactive Volume Navigation
Volume navigation is the interactive exploration of volume data sets by "flying" the viewpoint through the data, producing a volume rendered view at each frame. We present an inexpensive perspective volume navigation method designed to be run on a PC platform with accelerated 3D graphics hardware. The heart of the method is a two-phase perspective ray casting algorithm that takes advantage of the coherence inherent in adjacent frames during navigation. The algorithm generates a sequence of approximate volume-rendered views in a fraction of the time that would be required to compute them individually. The algorithm handles arbitrarily large volumes by dynamically swapping data within the current view frustum into main memory as the viewpoint moves through the volume. We also describe an interactive volume navigation application based on this algorithm. The application renders gray-scale, RGB, and labeled RGB volumes by volumetric compositing, allows trilinear interpolation of sample points, and implements progressive refinement during pauses in user input.
18230962
Efficient and effective array bound checking
Array bound checking refers to determining whether all array references in a program are within their declared ranges. This checking is critical for software verification and validation because subscripting arrays beyond their declared sizes may produce unexpected results, security holes, or failures. It is available in most commercial compilers but current implementations are not as efficient and effective as one may have hoped: (1) the execution times of array bound checked programs are increased by a factor of up to 5, (2) the compilation times are increased, which is detrimental to development and debugging, (3) the related error messages do not usually carry information to locate the faulty references, and (4) the consistency between actual array sizes and formal array declarations is not often checked.This article presents two optimization techniques that deal with Points 1, 2, and 3, and a new algorithm to tackle Point 4, which is not addressed by the current literature. The first optimization technique is based on the elimination of redundant tests, to provide very accurate information about faulty references during development and testing phases. The second one is based on the insertion of unavoidable tests to provide the smallest possible slowdown during the production phase. The new algorithm ensures the absence of bound violations in every array access in the called procedure with respect to the array declarations in the calling procedure. Our experiments suggest that the optimization of array bound checking depends on several factors, not only the percentage of removed checks, usually considered as the best improvement measuring metrics. The debugging capability and compile-time and run-time performances of our techniques are better than current implementations. The execution times of SPEC95 CFP benchmarks with range checking added by PIPS, our Fortran research compiler, are slightly longer, less than 20%, than that of unchecked programs. More problems due to functional and data recursion would have to be solved to extend these results from Fortran to other languages such as C, C++, or Java, but the issues addressed in this article are nevertheless relevant.
14226937
Self-Learning IP Traffic Classification Based on Statistical Flow Characteristics
A number of key areas in IP network engineering, management and surveillance greatly benefit from the ability to dynamically identify traffic flows according to the applications responsible for their creation. Currently such classifications rely on selected packet header fields (e.g. destination port) or application layer protocol decoding. These methods have a number of shortfalls e.g. many applications can use unpredictable port numbers and protocol decoding requires high resource usage or is simply infeasible in case protocols are unknown or encrypted. We propose a framework for application classification using an unsupervised machine learning (ML) technique. Flows are automatically classified based on their statistical characteristics. We also propose a systematic approach to identify an optimal set of flow attributes to use and evaluate the effectiveness of our approach using captured traffic traces.
17197783
Multiple sender distributed video streaming
With the explosive growth of video applications over the Internet, many approaches have been proposed to stream video effectively over packet switched, best-effort networks. We propose a receiver-driven protocol for simultaneous video streaming from multiple senders to a single receiver in order to achieve higher throughput, and to increase tolerance to packet loss and delay due to network congestion. Our receiver-driven protocol employs a novel rate allocation algorithm (RAA) and a packet partition algorithm (PPA). The RAA, run at the receiver, determines the sending rate for each sender by taking into account available network bandwidth, channel characteristics, and a prespecified, fixed level of forward error correction, in such a way as to minimize the probability of packet loss. The PPA, run at the senders based on a set of parameters estimated by the receiver, ensures that every packet is sent by one and only one sender, and at the same time, minimizes the startup delay. Using both simulations and Internet experiments, we demonstrate the effectiveness of our protocol in reducing packet loss.
6207354
Development of Some Methods and Tools for Discovering Conceptual Knowledge
This abstract summarizes key points of our ongoing project that aims at developing several new methods in knowledge discovery in databases (KDD) and implementing them together with related techniques in an interactive-graphic environment. This research lies in several areas if KDD such as supervised classi fication, conceptual clustering, discovery of association rules, parallel and distributed data mining, genetic programming. Some of them are the continuation of our work done so far [1], [2], [3], and some others have been started recently