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Traditional approaches to receiver-driven layered multicast apply coarse-grain layered congestion control, which enables each receiver to adjust its receiving rate to match the available bandwidth. However, this restricts the scalability of fine-grain scalable video coding. In this paper, we present an approach that facilitates bandwidth inference congestion control in a hybrid coarse/fine layered multicast scheme for multimedia delivery. One-way delay trend detection has proven effective in explicitly or implicitly estimating end-to-end available bandwidth. Using a hierarchical layered probing scheme and a delay trend detection method, we have developed a congestion control protocol for fine-grain layered multicast. Combining this protocol with scalable video coding, we present a framework that achieves efficient scalable video streaming over heterogeneous networks. The performance of our hybrid coarse/fine layered multicast scheme is evaluated by network simulations and the video coding efficiency. Index Terms--Available bandwidth estimation, congestion control, hybrid coarse/fine layered multicast.

Inspired by Paragious and Deriche's work, which unities boundary-based and region-based image partition approaches, we integrate the snake model and the Fisher criterion to capture, respectively, the boundary information and region information of microarray images. We then use the proposed algorithm to segment the spots in the microarray images, and compare our results with those obtained by commercial software. Our algorithm is automatic because the parameters are adaptively estimated from the data without human intervention. Index Terms--Microarray image, spot segmentation.

In this paper, we propose a systematic approach that approximates a target dictionary to reduce the complexity of a matching pursuit encoder. We combine calculation of the inner products and maximum atom extraction of a matching pursuit video coding scheme based on eigendictionary approximation and tree-based vector quantization. The approach makes the codec design and optimization cleaner and more systematic than previous dictionary approximation methods. We vary the quality of approximation to demonstrate the tradeoff between computational complexity and coding efficiency. The experiment results show that our codec achieves speed-up factors of up to 100 with a performance loss of less than 0.1 dB. We use double-stimulus impairment scale scores to evaluate the perceptual quality of our approach for different levels of complexity. Index Terms--Fast algorithm, matching pursuit (MP), tree-based vector quantization (VQ), video coding.

We compare, both objectively and subjectively, the performance of various advanced motion compensation methods, including overlapped block motion compensation (OBMC) and control grid interpolation (CGI), in a 3-D wavelet-based coding system. The motion vectors of the methods are obtained by using a sequence of 1-D dynamic programming algorithms that minimizes the cost function. Our experiment results indicate that an OBMC sequence usually has a higher peak signal-to-noise ratio (PSNR) than other methods, while a CGI sequence usually contains the fewest blocking artifacts. We provide a simple framework that combines the OBMC and CGI sequences. The proposed hybrid method removes more than 50% of the blocking artifacts of an OBMC sequence, while simultaneously maintaining a high PSNR performance. Index Terms--Control grid interpolation (CGI), overlapped block motion compensation (OBMC), wavelet transform.

Because channel capacity varies depending on network traffic and the capacity of each reception, fine granularity scalability (FGS) of video coding has emerged as an important area in multimedia streaming applications. We propose an FGS video codec and a two-layer signal-to-noise ratio (SNR) scalable video codec, based on matching pursuits and bitplane coding. The temporal and spatial redundancy of atom positions between adjacent bitplanes are explored using the quadtree representation for a bitplane and the quadtree prediction algorithm. The efficiency of encoding atom positions is evaluated. Our FGS combines successive bitplane quantization of atom modula and quadtree prediction of atom positions. The performance of our FGS is compared with that of the discrete-cosine-transform-based FGS codec. The quality of a base layer or enhancement layer video in a two-layer scalable video codec can be adjusted without changing the bit rates. We propose using a combined frame obtained from the combination of the reconstructed base layer and enhancement layer images to estimate motion vectors. The performance of our two-layer codec is illustrated. Index Terms--Fine granularity scalability (FGS), matching pursuits (MPs), two-layer, streaming.

A subspace watermarking method is described in which an optimum subspace watermarking method, from which a watermark sequence is selected for the image is obtained using a Monte Carlo simulation of pirate attacks on the image.

A new parameter estimation algorithm and a new signal estimation algorithm for a fractional Brownian motion (fBm) embedded in white noise are presented. Neither of the algorithms demand the exclusive use of orthogonal wavelets which offer an effective wavelet representation for applications where the fractal estimation and other signal features are to be processed simultaneously. Results indicate that the proposed algorithms are very advantageous if the wavelet basis serves multiple purposes in both feature extraction and fractal estimation.

This paper proposes an automatic eye-wink interpretation system for human-machine interface to benefit the severely handicapped people. Our system consists of (1) applying the support vector machine (SVM) to detect the eyes, (2) using the template matching algorithm to track the eyes, (3) using SVM classifier to verify the open or closed eyes and convert the eye winks into a sequence of codes (0 or 1), and (4) applying the dynamic programming to translate the code sequence to a certain valid command. Different from the previous eye-gaze tracking methods, our system identifies the open or closed eye, and then interprets the eye winking as certain commands for human-machine interface. In the experiments, our system demonstrates better performance as well as higher accuracy.