Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2005. / Includes bibliographical references (leaves 76-82). Also available in electronic version.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2005. / Includes bibliographical references (leaves 103-106). Also available in electronic version.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2006. / Includes bibliographical references (leaves 72-75). Also available in electronic version.

Theses (M.S.)--Marshall University, 2006. / Title from document title page. Includes abstract. Document formatted into pages: contains ix, 99 pages. Bibliography: p. 97-99.

Thesis (M.Phil.)--Hong Kong University of Science and Technology, 2007. / Includes bibliographical references (leaves 86-90). Also available in electronic version.

Advances in digital technology in the last decade have motivated the development of very efficient and high quality speech compression algorithms. While in the early low bit rate coding systems, the main target was production of intelligible speech at low information rates, expansion of new applications such as mobile satellite systems increased the demand for high quality speech at lowest possible bit rates. This resulted in the development of efficient parametric models for speech production system. These models were the basis of powerful speech compression algorithms such as CELP and Multiband excitation. CELP is a very efficient algorithm at medium bit rates and has achieved almost toll quality at 8 kb/s. However, the performance of CELP rapidly reduces at bit rates below 4.8 kb/s. The sinusoidal based coding algorithms and in particular multiband excitation technique have proved their abilities in producing high quality speech at bit rates below 5 kb/s. In recent years, another efficient speech compression algorithm called prototype waveform interpolation (PWI) has emerged. PWI presented a novel model which proved to be very efficient in removing redundant information from speech. While the early PWI systems produced high quality speech at bit rates around 3.5 kb/s, its latest versions produce an even higher quality at the bit rates as low as 2.4 kb/s. The key to the success of PWI is the approach it exploits in reducing the distortion associated with low bit rate coding algorithms. However, the price for this achievement is a very high computational demand which has been the main hurdle in its real time applications. The aim of the research in this thesis is the development of low complexity PWI systems without sacrificing the high quality. While the target of the majority of PWI systems is efficient coding of the excitation signal in the LP model of speech, this research focuses on exploiting PWI to directly encode the original speech. In the first part of the thesis, basic techniques in low bit rate speech coding are described and proper tools are developed to be exploited in a PWI based coding system. In the second part, the original PWI algorithm operating in the LP residual domain is briefly explained and application of PWI in speech domain is introduced as a method to cope with problems associated with the original PWI. To demonstrate the abilities of this approach, various coding schemes operating in the range of 1.85 to 2.95 kb/s are developed. In the final stage, a new technique which combines the two powerful low bit rate coding techniques, i.e multiband excitation and PWI, is developed to produce high quality synthetic speech at 2.6 kb/s.

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<p>Image compression is widely applied to medical imaging, remote sensing applications, biomedical diagnosis, multimedia applications and so on [1]-[4]. In many cases, considering the factor of image quality, we use a lossless compression method to compress the image.</p> <p>In this thesis work, we propose bit-error aware lossless compression algorithms for color image compression subject to bit-error rate during transmission. Each of our proposed algorithms includes three stages. The first stage is to convert the RGB images to YCrCb images, and the second stage predicts the transformed images to generate the residue sequences. Optimization algorithms are used to search the best combination of the image conversion and prediction. At the last stage, <a>the generated residue sequences are encoded by several residue coding algorithms, which are 2-D and 1-D bi-level block coding, interval Huffman coding and standard Huffman coding algorithms</a>. Key parameters, such as color transformation information, predictor parameters and residue coding parameters, are protected by using (7,4) Hamming code during image transmission, </p> <p><a>The compression ratio (CR) and peak signal to noise ratio (PSNR)</a> are two significant performance indicators which are used to evaluate the experimental results. According to the experimental results, the 2-D bi-level block coding algorithm is verified as the best coding method.</p>

As technology has advanced, data has become more and more important. The more breakthroughs are achieved, the more data is needed to support them. As a result, more storage is required in the system's memory. Compression is therefore required. Before it can be stored, the data must be compressed. To ensure that information is not lost, efficient compression is necessary. This also makes sure that there is no redundancy in the data that is being kept and stored. Compressive sensing has emerged as a new field of compression thanks to developments in sparse optimization. Rather than relying just on compression and sensing formulations, the theory blends the two. The objective of this thesis is to analyze the concept of compressive sensing and to study several reconstruction algorithms. Additionally, a few of the algorithms were put into practice. This thesis also included a model of the ECG, which is vital in determining the health of the heart. For the most part, the ECG is utilized to diagnose heart illness, and a modified synthetic ECG can be used to mimic some of these arrhythmias.

A method for compressing surfaces associated with C1 cubic splines defined on triangulated quadrangulations is described. The method makes use of hierarchical bases, and does not require the construction of wavelets.