Thesis (Ph.D.)--City University of Hong Kong, 2004. / "Submitted to Department of Computer Science in partial fulfillment of the requirements for the degree of Doctor of Philosophy" Includes bibliographical references (leaves 145-158)

Thesis (Ph. D.)--Lehigh University, 1998. / Includes vita. Bibliography: leaves 139-143.

Thèses (M.Sc.A.)--Université de Sherbrooke (Canada), 1997. / Titre de l'écran-titre (visionné le 20 juin 2006). Publié aussi en version papier.

Thèses (M.Sc.A.)--Université de Sherbrooke (Canada), 2000. / Titre de l'écran-titre (visionné le 20 juin 2006). Publié aussi en version papier.

Thèses (M.Sc.A.)--Université de Sherbrooke (Canada), 2003. / Titre de l'écran-titre (visionné le 20 juin 2006). Publié aussi en version papier.

With the evolution of multimedia systems, image and video compression is becoming the key enabling technology for delivering various image/video services over heterogeneous networks. The basic goal of image data compression is to reduce the bit rate for transmission and storage while either maintaining the original quality of the data or providing an acceptable quality. This thesis proposes a new wavelet transform for lossless compression of images with application to medical images. The transform uses integer arithmetic and is very computationally efficient. Then a new color image transformation, which is reversible and uses integer arithmetic, is proposed. The transformation reduces the redundancy among the red, green, and blue color bands. It approximates the luminance and chrominance components of the YIQ coordinate system. This transformation involves no floating point/integer multiplications or divisions, and is, therefore, very suitable for real-time applications where the number of CPU cycles needs to be kept to a minimum. A technique for lossy compression of an image data base is also proposed. The technique uses a wavelet transform and vector quantization for compression. The discrete cosine transform is applied to the coarsest scale wavelet coefficients to achieve even higher compression ratios without any significant increase in computational complexity. Wavelet denoising is used to reduce the image artifacts generated by quantizing the discrete cosine transform coefficients. This improves the subjective quality of the decompressed images for very low bit rate images (less than 0.5 bits per pixel). The thesis also deals with the real-time implementation of the wavelet transform. The new wavelet transform has been applied to speech signals. Both lossless and lossy techniques for speech coding have been implemented. The lossless technique involves using the reversible integer-arithmetic wavelet transform and Huffman coding to obtain the compressed bitstream. The lossy technique, on the other hand, quantizes the wavelet coefficients to obtain higher compression ratio at the expense of some degradation in sound quality. The issues related to real-time wavelet compression are also discussed. Due to the limited size of memory on a DSP, a wavelet transform had to be applied to an input signal of finite length. The effects of varying the signal length on compression performance are also studied for different reversible wavelet transforms. The limitations of the proposed techniques are discussed and recommendations for future research are provided. / Graduate

The scope of the present dissertation is a deep lossy compression of still and moving grayscale pictures while maintaining their fidelity, with a specific goal of creating a working prototype of a software system for use in low bandwidth transmission of still satellite imagery and weather briefings with the best preservation of features considered important by the end user.

A new progressive lossy-to-lossless coding framework for 2.5-dimensional (2.5-D) triangle meshes with arbitrary connectivity is proposed by combining ideas from the previously proposed average-difference image-tree (ADIT) method and the Peng-Kuo (PK) method with several modifications. The proposed method represents the 2.5-D triangle mesh with a binary tree data structure, and codes the tree by a top-down traversal. The proposed framework contains several parameters. Many variations are tried in order to find a good choice for each parameter considering both the lossless and progressive coding performance. Based on extensive experimentation, we recommend a particular set of best choices to be used for these parameters, leading to the mesh-coding method proposed herein / Graduate

File carving is a technique used to recover data from a digital device without the help of file system metadata. The current file carvers use techniques such as using a list of header and footer values and key word searching to retrieve the information specific to a file type. These techniques tend to fail when the files to be recovered are fragmented. Recovering the fragmented files is one of the primary challenges faced by file carving. In this research we focus on Variable Bit Rate (VBR) MP3 files. MP3 is one of the most widely used file formats for storing audio data. We develop a technique which uses the MP3 file structure information to improve the performance of file carvers in reconstructing fragmented MP3 data. This technique uses a large number of MP3 files and performs statistical analysis on the bitrates of these files.

This thesis investigates motion-adaptive temporal transformations and motion parameter coding schemes, for highly scalable video compression. The first aspect of this work proposes a new framework for constructing temporal discrete wavelet transforms, based on motion-compensated lifting steps. The use of lifting preserves invertibility regardless of the selected motion model. By contrast, the invertibility requirement has restricted previous approaches to either block-based or global motion compensation. We show that the proposed framework effectively applies the temporal wavelet transform along the motion trajectories. Video sequences reconstructed at reduced frame-rates, from subsets of the compressed bitstream, demonstrate the visually pleasing properties expected from lowpass filtering along the motion trajectories. Experimental results demonstrate the effectiveness of temporal wavelet kernels other than the simple Haar. We also demonstrate the benefits of complex motion modelling, by using a deformable triangular mesh. These advances are either incompatible or diffcult to achieve with previously proposed strategies for scalable video compression. A second aspect of this work involves new methods for the representation, compression and rate allocation of the motion information. We first describe a compact representation for the various motion mappings associated with the proposed lifting transform. This representation significantly reduces the number of distinct motion fields that must be transmitted to the decoder. We also incorporate a rate scalable scheme for coding the motion parameters. This is achieved by constructing a set of quality layers for the motion information, in a manner similar to that used to construct the scalable sample representation. When the motion layers are truncated, the decoder receives a quantized version of the motion parameters used to code the sample data. A linear model is employed to quantify the effects of motion parameter quantization on the reconstructed video distortion. This allows the optimal trade-off between motion and subband sample bit-rates to be determined after the motion and sample data has been compressed. Two schemes are proposed to determine the optimal trade-off between motion and sample bit-rates. The first scheme employs a simple but effective brute force search approach. A second scheme explicitly utilizes the linear model, and yields comparable performance to the brute force scheme, with significantly less computational cost. The high performance of the second scheme also serves to reinforce the validity of the linear model itself. In comparison to existing scalable coding schemes, the proposed video coder achieves significantly higher compression performance, and motion scalability facilitates effcient compression even at low bit-rates. Experimental results show that the proposed scheme is also competitive with state-of-the-art non-scalable video coders.