An embedded still image coder with rate-distortion optimization
It is well known that the fixed rate coder achieves optimality when all coefficients are coded with the same rate-distortion (R-D) slope. In this paper, we show that the performance of the embedded coder can be optimized in a rate-distortion sense by coding the coefficients with decreasing R-D slope. We denote such a coding strategy as rate-distortion optimized embedding (RDE). RDE allocates the available coding bits first to the coefficient with the steepest R-D slope, i.e., the largest distortion decrease per coding bit. The resultant coding bitstream can be truncated at any point and still maintain an optimal R-D performance. To avoid the overhead of coding order transmission, we use the expected R-D slope, which can be calculated from the coded bits and is available in both the encoder and the decoder. With the probability estimation table of the QM-coder, the calculation of the R-D slope can be just a lookup table operation. Experimental results show that the rate-distortion optimization significantly improves the coding efficiency in a wide bit rate range.

title: Motion compensated lifting wavelet and its application in video coding
abstract: A motion compensated lifting (MCLIFT) framework is proposed for the 3D wavelet video coder. By using bi-directional motion compensation in each lifting step of the temporal direction, the video frames are effectively de-correlated. With proper entropy coding and bitstream packaging schemes, the MCLIFT wavelet video coder can be scalable in frame rate and quality level. Experimental results show that the MCLIFT video coder outperforms the 3D wavelet video coder with the same entropy coding scheme by an average of 1.1-1.6dB, and outperforms MPEG-4 coder by an average of 0.9-

title: Compression of the layered depth image
abstract: A layered depth image (LDI) is a new popular representation and rendering method for objects with complex geometries. Similar to a 2D image, the LDI consists of an array of pixels. However, unlike the 2D image, an LDI pixel has depth information, and there are multiple layers at a pixel location. In this paper, we develop a novel LDI compression algorithm that handles the multiple layers and the depth coding. The algorithm records the number of LDI layers at each pixel location, and compresses LDI color and depth components separately. For LDI layer with sparse pixels, the data is aggregated and then encoded. An empirical rate-distortion model is used to optimally allocate bits among different components. Compared with benchmark compression tools such as JPEG-2000 and MPEG-4, our scheme improves the compression performance significantly.

title: On the compression and streaming of concentric mosaic data for free wandering in a realistic environment over the Internet
abstract: In this paper, we describe a system for wandering in a realistic environment over the Internet. The environment is captured by the concentric mosaic, compressed via the reference block coder (RBC), and accessed and delivered over the Internet through the virtual media (Vmedia) access protocol. One of the key contributions of the paper is the proposal of the RBC concentric mosaic coder. The RBC coder not only compresses the huge dataset of the concentric mosaic very efficiently, but also produces a well-organized bitstream that can be accessed just-in-time (JIT). To reconstruct a virtual view, only a portion of the RBC bitstream needs to be accessed and decoded. This greatly reduces the memory and computation requirement of the viewer compared with first decoding the entire concentric mosaic data set and then rendering from the decoded data. Our second contribution is the employment of the Vmedia protocol to deliver the compressed concentric mosaic bitstream just-in-time over the Internet. Only the bitstream segments corresponding to the current view are streamed over the Internet. The delivered bitstream segments are managed by a local Vmedia cache, so that frequently used bitstream segments do not need to be streamed over the Internet repeatedly, and a RBC bitstream larger than the memory capacity can be easily handled. Combining RBC and Vmedia, a concentric mosaic interactive browser is developed through which the user can freely wander in a realistic environment, e.g., rotate around, walk forward/backward, and sidestep, even under a tight bandwidth.

title: Distributed hosting of Web content with erasure coding and unequal weight assignment
abstract: By sharing and hosting personal Web content in a peer-to-peer (P2P) fashion, we may increase the bandwidth of retrieval and improve the reliability of retrieval. The cost is that the Web content has to be replicated to and stored in the peers, consuming valuable network bandwidth and peer storage space. In this work, we develop two technologies, namely hierarchical content organization with unequal weight assignment and erasure coding, to reduce the amount of content to be distributed, yet still maintain the retrieval speed up and reliability. Significant improvement over the ordinary Web server is demonstrated.

title: Compression of Lumigraph with multiple reference frame (MRF) prediction and just-in-time rendering
abstract: In the form of a 2D image array, Lumigraph captures the complete appearance of an object or a scene, and is able to quickly render a novel view independent of the scene/object complexity. Since the data amount of Lumigraph is huge, efficient storage and access for Lumigraph are essential. In this paper, we propose a multiple reference frame (MRF) structure to compress the Lumigraph data. By predicting the Lumigraph view from multiple neighbor views, a higher compression ratio is achieved. We also implement the key functionality of just-in-time (JIT) Lumigraph rendering, in which only a small portion of the compressed bitstream necessary for rendering the current view is accessed and decoded. JIT rendering eliminates the need to predecode the entire Lumigraph data set, thus greatly reduces the memory requirement of Lumigraph rendering. A decoder cache has been implemented to speed up rendering by reusing the decoded data. The trade off between the computational speed and cache size of the decoder is discussed in the paper.

title: Evolvable Fuzzy System for ATM Cell Scheduling
abstract: In this paper, we propose an evolvable fuzzy system for ATM cell scheduling. When the scenarios of cell flows in an ATM network change dramatically, traditional scheduling algorithms, first-in-first-out (FIFO) and static priority, which employ static switching scheme may see their efficiency deteriorate. An alternative is to use dynamically weighted priority, which changes the priority based on the cell delay. Still, the algorithm per se is fixed and on the hardware level, nothing changes. Our goal in this paper is to achieve hardware adaptability and demonstrate its applicability in ATM switching. To do this, we proposed an evolvable fuzzy system . With evolvable fuzzy system (EFS), the system undergoes transformation in response to changes in the cell patterns in order to maintain operational efficiency. We envisage that such a system is potentially useful for demanding real-time dynamic control applications.

title: Context-based multiscale classification of document images using wavelet coefficient distributions
abstract: In this paper, an algorithm is developed for segmenting document images into four classes: background, photograph, text, and graph. Features used for classification are based on the distribution patterns of wavelet coefficients in high frequency bands. Two important attributes of the algorithm are its multiscale nature-it classifies an image at different resolutions adaptively, enabling accurate classification at class boundaries as well as fast classification overall-and its use of accumulated context information for improving classification accuracy.

title: Securing distributed adaptation
abstract: Open architecture networks provide applications with fine-grained control over network elements. With this control comes the risk of misuse and new challenges to security beyond those present in conventional networks. One particular security requirement is the ability of applications to protect the secrecy and integrity of transmitted data while still allowing trusted active elements within the network to operate on that data. This paper describes mechanisms for identifying trusted nodes within a network and securely deploying adaptation instructions to those nodes while protecting application data from unauthorized access and modification. Promising experimental results of our implementation within the conductor adaptation framework are also presented, suggesting that such features can be incorporated into real networks.

title: Parameter estimation of multi-dimensional hidden Markov models - a scalable approach
abstract: Parameter estimation is a key computational issue in all statistical image modeling techniques. In this paper, we explore a computationally efficient parameter estimation algorithm for multi-dimensional hidden Markov models. 2-D HMM has been applied to supervised aerial image classification and comparisons have been made with the first proposed estimation algorithm. An extensive parametric study has been performed with 3-D HMM and the scalability of the estimation algorithm has been discussed. Results show the great applicability of the explored algorithm to multi-dimensional HMM based image modeling applications.

title: A new Mallows distance based metric for comparing clusterings
abstract: Despite of the large number of algorithms developed for clustering, the study on comparing clustering results is limited. In this paper, we propose a measure for comparing clustering results to tackle two issues insufficiently addressed or even overlooked by existing methods: (a) taking into account the distance between cluster representatives when assessing the similarity of clustering results; (b) constructing a unified framework for defining a distance based on either hard or soft clustering and ensuring the triangle inequality under the definition. Our measure is derived from a complete and globally optimal matching between clusters in two clustering results. It is shown that the distance is an instance of the Mallows distance---a metric between probability distributions in statistics. As a result, the defined distance inherits desirable properties from the Mallows distance. Experiments show that our clustering distance measure successfully handles cases difficult for other measures.