الفهرس 
signal compressionOnly 14 pages are availabe for public view
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Abstract
The digital representation of an image requires a very large number of bits. The goal of image coding is to reduce this number, as much as possible, and reconstruct a faithful duplicate of the original picture. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio, starting with the first digital picture in the early 1960s, reached a solution level around 10: 1 a couple of years ago. This certainly does not mean that the upper bound given by the entropy of the source has also been reached. First, this entropy is not known and depends heavily on the model used for the source, Second, the information theory does not take into account the biological nature of the human eye. Recent progress in the study of the brain mechanism of vision has opened new vistas in picture coding. Directional sensitivity of the neurones in the visual pathway combined with the separate processing of contents and textures has led to a new class of coding methods capable of achieving compression ratios as high as 70 : 1. Image quality, of course, remains as an important problem to be investigated.
The transformation is one of the most famous technique used in signal compression which proves good performance in achieving high compression ratio. In the second chapter, a brief mathematical background about the transformation technique is introduced to give a necessary idea about the formulas and the fastening methods used in transform operation. Firstly, a brief note about all types of the transformation techniques are discussed. Then, the famous discrete transformation techniques are studied carefully. Discrete Fourier transform formulas, the fast Fourier transform, and the bidimensional discrete Fourier transform are driven and concluded. Same topics are also clarified for discrete cosine transform. Finally the discrete wavelet transform is introduced as the state-of-the art technique of transformation.
In the third chapter, the sub coding system in signal processing will be discussed. Before using this system, the whole input signal was decoded with the same coding word length regardless to the power distribution among the bands of its spectrum. The common coding word length is always chosen to match the band having the highest power. It means that the other bands have a coding word length longer than the sufficient length required to represent their information. The subcoding