الفهرس 
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Abstract
ABSTRACT
The Subband Coding (SBC) and Wavelet Transform (WT) are widely used in the area of signal processing and communication as speech and image coding techniques. We review the subband coding, the different structures of filter banks and the design of these filter banks using FIR Quadrature Mirror Filters (QMF). We present the design of fiR QMF and discuss its stability.
The Wavelet Transform (WT) and the computation algorithms of the Discrete Wavelet Transform (DWT) will be reviewed. The relation between the DWT and the subband coding is discussed and we present the conversion algorithms between these two techniques.
Both SBC and DWT deal with the speech as 1 dimension (lD) signal and image as 2 dimension (2D) signal so we review the conventional algorithms used in the speech and image coding. We present a process that can be applied on the image so it gives us the ability to use the same algorithm on both speech and image signals. Finally, we propose a complete system that achieves this method.
This thesis consists of seven chapters organized as follows:
Chapter 1 represents the different coding techniques either in time- or in frequency¬domain. It explains the importance of the digital data compression and its applications. It discusses the speech compression and the requirements of the low bit rate coders. It represents the image compression and its applications. Finally it shows the aim of this thesis.
Chapter 2 makes a survey on the further works in the subband coding using different digital filter bank structures and in the wavelet transform using different computation algorithms. It reviews relation between these two techniques.
Chapter 3 briefly reviews the different structures of QMF banks such as: 2-band, tree¬structure and M-band maximally decimated QMF bank. The design of the latter one is
discussed by using different algorithms. It shows the design algorithms of these ftlters in terms of FIR and IIR filters. This chapter describs the used subband coding algorithm that is applied on the image. It presents two methods the non-separable methods and separable methods and compares between them.
Chapter 4 presents the principles of wavelet transform and its types. It discusses the discrete wavelet transform in detail and shows the generation of the mother wavelet and different algorithms that used in computing the DWT values. It studies Mallat algorithm carefully and its applications on ID signals and 2D signals.
Chapter 5 presents the results obtained from applying the subband coding and wavelet transform on speech signals. The results are obtained by using the fixed and dynamic bit allocation with different digital filter structure (tree-stucture and M-band) using FIR and IIR filters. For wavelet transform, Mallat algorithm is applied to reduce the bit rate using fixed or dynamic bit allocation.
Chapter 6 presents the results obtained from the applying of the sub band coding and wavelet transform on the image. The input gray images are square having 128 gray levels. We deal with these images as a matrix in MATLAB software.
We test the conversion of the 2D image signal into ID signal then we apply the ID algorithms. In this chapter, we will present the results of each method and then we compare between them.
Chapter 7 discusses the obtained results from applying the sub band coding and wavelet transform as coding techniques for both speech and image signals. We propose a system that can be applied on speech and image and deal with them by the same manner and the same algorithm. Finally, this chapter presents suggestions for future work.