Models and analysis of vocal emissions for biomedical applications

This book of Proceedings collects the papers presented at the 3rd International Workshop on Models and Analysis of Vocal Emissions for Biomedical Applications, MAVEBA 2003, held 10-12 December 2003, Firenze, Italy. The workshop is organised every two years, and aims to stimulate contacts between specialists active in research and industrial developments, in the area of voice analysis for biomedical applications. The scope of the Workshop includes all aspects of voice modelling and analysis, ranging from fundamental research to all kinds of biomedical applications and related established and advanced technologies

Error relilient video communications using high level M-QAM. Modelling and simulation of a comparative analysis of a dual-priority M-QAM transmission system for H.264/AVC video applications over band-limited and error-phone channels.

An experimental investigation of an M level (M = 16, 64 and 256) Quadrature Amplitude Modulation (QAM) transmission system suitable for video transmission is presented. The communication system is based on layered video coding and unequal error protection to make the video bitstream robust to channel errors. An implementation is described in which H.264 video is protected unequally by partitioning the compressed data into two layers of different visual importance. The partition scheme is based on a separation of the group of pictures (GoP) in the intra-coded frame (I-frame) and predictive coded frame (P frame). This partition scheme is then applied to split the H.264-coded video bitstream and is suitable for Constant Bit Rate (CBR) transmission. Unequal error protection is based on uniform and non-uniform M-QAM constellations in conjunction with different scenarios of splitting the transmitted symbol for protection of the more important information of the video data; different constellation arrangements are proposed and evaluated to increase the capacity of the high priority layer. The performance of the transmission system is evaluated under Additive White Gaussian Noise (AWGN) and Rayleigh fading conditions. Simulation results showed that in noisy channels the decoded video can be improved by assigning a larger portion of the video data to the enhancement layer in conjunction with non-uniform constellation arrangements; in better channel conditions the quality of the received video can be improved by assigning more bits in the high priority channel and using uniform constellations. The aforementioned varying conditions can make the video transmission more successful over error-prone channels. Further techniques were developed to combat various channel impairments by considering channel coding methods suitable for layered video coding applications. It is shown that a combination of non-uniform M-QAM and forward error correction (FEC) will yield a better performance. Additionally, antenna diversity techniques are examined and introduced to the transmission system that can offer a significant improvement in the quality of service of mobile video communication systems in environments that can be modelled by a Rayleigh fading channel

SSIM-Inspired Quality Assessment, Compression, and Processing for Visual Communications

Objective Image and Video Quality Assessment (I/VQA) measures predict image/video quality as perceived by human beings - the ultimate consumers of visual data. Existing research in the area is mainly limited to benchmarking and monitoring of visual data. The use of I/VQA measures in the design and optimization of image/video processing algorithms and systems is more desirable, challenging and fruitful but has not been well explored. Among the recently proposed objective I/VQA approaches, the structural similarity (SSIM) index and its variants have emerged as promising measures that show superior performance as compared to the widely used mean squared error (MSE) and are computationally simple compared with other state-of-the-art perceptual quality measures. In addition, SSIM has a number of desirable mathematical properties for optimization tasks. The goal of this research is to break the tradition of using MSE as the optimization criterion for image and video processing algorithms. We tackle several important problems in visual communication applications by exploiting SSIM-inspired design and optimization to achieve significantly better performance. Firstly, the original SSIM is a Full-Reference IQA (FR-IQA) measure that requires access to the original reference image, making it impractical in many visual communication applications. We propose a general purpose Reduced-Reference IQA (RR-IQA) method that can estimate SSIM with high accuracy with the help of a small number of RR features extracted from the original image. Furthermore, we introduce and demonstrate the novel idea of partially repairing an image using RR features. Secondly, image processing algorithms such as image de-noising and image super-resolution are required at various stages of visual communication systems, starting from image acquisition to image display at the receiver. We incorporate SSIM into the framework of sparse signal representation and non-local means methods and demonstrate improved performance in image de-noising and super-resolution. Thirdly, we incorporate SSIM into the framework of perceptual video compression. We propose an SSIM-based rate-distortion optimization scheme and an SSIM-inspired divisive optimization method that transforms the DCT domain frame residuals to a perceptually uniform space. Both approaches demonstrate the potential to largely improve the rate-distortion performance of state-of-the-art video codecs. Finally, in real-world visual communications, it is a common experience that end-users receive video with significantly time-varying quality due to the variations in video content/complexity, codec configuration, and network conditions. How human visual quality of experience (QoE) changes with such time-varying video quality is not yet well-understood. We propose a quality adaptation model that is asymmetrically tuned to increasing and decreasing quality. The model improves upon the direct SSIM approach in predicting subjective perceptual experience of time-varying video quality