A Family of Hierarchical Encoding Techniques for Image and Video Communications

As the demand for image and video transmission and interactive multimedia applications continues to grow, scalable image and video compression that has robust behavior over unreliable channels are of increasing interest. These desktop applications require scalability as a main feature due to its heterogeneous nature, since participants in an interactive multimedia application have different needs and processing power. Also, the encoding and decoding algorithm complexity must be low due to the practical considerations of low-cost low-power receiver terminals. This requires image and video encoding techniques that jointly considers compression, scalability, robustness, and simplicity. In this dissertation, we present a family of image and video-encoding techniques, which are developed to support conferencing applications. We achieve scalability, robustness and low computational complexity by building our encoding techniques based on the quadtree and octree representation methods. First we developed an image encoding technique using the quadtree representation of images and vector quantization. We use a mean-removal technique to separate the means image and the difference image. The difference image is then encoded as a breadth first traversal of the quadtree corresponding to the image. Vector quantization is then used to compress the quadtree nodes based on the spatial locality of the quadtree data. Our next step was to use the quadtree-based image encoding technique as a base for developing a differential video encoding technique. We extended it to encode video by applying the well-known IPB technique to the image encoding system. Then, we explore another method of extending our image encoding technique to encode video streams. The basic idea was to use exactly the same three steps used in our image encoding technique, mean removal, conversion to tree structure, and vector quantization, and replace the quadtree structure with an octree structure. The octree is the three-dimensional equivalent of the quadtree. We divide the sequence of frames into groups and view each group as a three-dimensional object. By encoding frames together, we can obtain substantial savings in encoding time and better compression results. Finally, we combined both the differential quadtree and octree approaches to generate a new hybrid encoding technique. We encode one frame using the quadtree-based image encoding technique, and then encode the following group of frames as a differential octree based upon the first frame. Using a set of experiments, the quadtree-based image encoding and differential video encoding techniques were shown to provide reasonable compression in comparison with similar techniques, while the octree and hybrid video encoding techniques gave impressive compression results. Furthermore, we demonstrated that our encoding techniques are time efficient compared to the more common frequency based techniques. We also compare their scalability feature favorably with other well-known scalable techniques. Moreover, we demonstrated their ability to tolerate and conceal error. The new encoding techniques proved to be efficient methods of encoding for interactive multimedia applications

Wavelet Based Image Coding Schemes : A Recent Survey

A variety of new and powerful algorithms have been developed for image compression over the years. Among them the wavelet-based image compression schemes have gained much popularity due to their overlapping nature which reduces the blocking artifacts that are common phenomena in JPEG compression and multiresolution character which leads to superior energy compaction with high quality reconstructed images. This paper provides a detailed survey on some of the popular wavelet coding techniques such as the Embedded Zerotree Wavelet (EZW) coding, Set Partitioning in Hierarchical Tree (SPIHT) coding, the Set Partitioned Embedded Block (SPECK) Coder, and the Embedded Block Coding with Optimized Truncation (EBCOT) algorithm. Other wavelet-based coding techniques like the Wavelet Difference Reduction (WDR) and the Adaptive Scanned Wavelet Difference Reduction (ASWDR) algorithms, the Space Frequency Quantization (SFQ) algorithm, the Embedded Predictive Wavelet Image Coder (EPWIC), Compression with Reversible Embedded Wavelet (CREW), the Stack-Run (SR) coding and the recent Geometric Wavelet (GW) coding are also discussed. Based on the review, recommendations and discussions are presented for algorithm development and implementation.Comment: 18 pages, 7 figures, journa

Advance of the Access Methods

The goal of this paper is to outline the advance of the access methods in the last ten years as well as to make review of all available in the accessible bibliography methods

Exploiting Location Awareness for Scalable Location-Independent Object IDs

We are building a wide-area location service that tracks the current location of mobile and replicated objects. The location service should support up to 10 12 objects on a worldwide scale. To support this huge number of objects, the workload of the location service is distributed over multiple hosts. Our load distribution method is unique in that it is aware of the (geographical) location of the hosts it uses. By using this location knowledge when distributing the workload, the distribution mechanism enforces locality of operations in the location service. Enforcing locality minimizes the use of global network resources by the location service and thereby enhances its scalability. We also show how this location-aware load distribution mechanism can be implemented. 1 Introduction Objects provide an easy way to model both applications and system services. It is therefore easy to understand that the use of objects as a design and implementation method has become popular, for example..

Visual Data Compression for Multimedia Applications

The compression of visual information in the framework of multimedia applications is discussed. To this end, major approaches to compress still as well as moving pictures are reviewed. The most important objective in any compression algorithm is that of compression efficiency. High-compression coding of still pictures can be split into three categories: waveform, second-generation, and fractal coding techniques. Each coding approach introduces a different artifact at the target bit rates. The primary objective of most ongoing research in this field is to mask these artifacts as much as possible to the human visual system. Video-compression techniques have to deal with data enriched by one more component, namely, the temporal coordinate. Either compression techniques developed for still images can be generalized for three-dimensional signals (space and time) or a hybrid approach can be defined based on motion compensation. The video compression techniques can then be classified into the following four classes: waveform, object-based, model-based, and fractal coding techniques. This paper provides the reader with a tutorial on major visual data-compression techniques and a list of references for further information as the details of each metho

RUBIK: Efficient Threshold Queries on Massive Time Series

An increasing number of applications from finance, meteorology, science and others are producing time series as output. The analysis of the vast amount of time series is key to understand the phenomena studied, particularly in the simulation sciences, where the analysis of time series resulting from simulation allows scientists to refine the model simulated. Existing approaches to query time series typically keep a compact representation in main memory, use it to answer queries approximately and then access the exact time series data on disk to validate the result. The more precise the in-memory representation, the fewer disk accesses are needed to validate the result. With the massive sizes of today's datasets, however, current in-memory representations oftentimes no longer fit into main memory. To make them fit, their precision has to be reduced considerably resulting in substantial disk access which impedes query execution today and limits scalability for even bigger datasets in the future. In this paper we develop RUBIK, a novel approach to compressing and indexing time series. RUBIK exploits that time series in many applications and particularly in the simulation sciences are similar to each other. It compresses similar time series, i.e., observation values as well as time information, achieving better space efficiency and improved precision. RUBIK translates threshold queries into two dimensional spatial queries and efficiently executes them on the compressed time series by exploiting the pruning power of a tree structure to find the result, thereby outperforming the state-of-the-art by a factor of between 6 and 23. As our experiments further indicate, exploiting similarity within and between time series is crucial to make query execution scale and to ultimately decouple query execution time from the growth of the data (size and number of time series)

Anatomical Modelling of the Musculoskeletal System from MRI

Abstract. This paper presents a novel approach for multi-organ (mus-culoskeletal system) automatic registration and segmentation from clini-cal MRI datasets, based on discrete deformable models (simplex meshes). We reduce the computational complexity using multi-resolution forces, multi-resolution hierarchical collision handling and large simulation time steps (implicit integration scheme), allowing real-time user control and cost-efficient segmentation. Radial forces and topological constraints (at-tachments) are applied to regularize the segmentation process. Based on a medial axis constrained approximation, we efficiently characterize shapes and deformations. We validate our methods for the hip joint and the thigh (20 muscles, 4 bones) on 4 datasets: average error=1.5mm, computation time=15min.