Transforms and Subband Decomposition
The properties of the audio and video signals, and the digitization process have been discussed in the previous Chapters. When a signal is digitized, further processing of these signals may be needed for various applications, such as compression, and enhancement. The processing of multimedia signal can be done effectively when the limitation of our hearing or visual systems is taken into account. For example, it was shown in Chapter 3 that the human ear is not very sensitive to audio signals with frequencies above 10–12 KHz. Similarly, the eyes also do not respond well above 20 cycles/degree. This dependency of our sensory systems on the frequency spectrum of the audio or visual signals has led to the development of transform and subband-based signal processing techniques. In these techniques, the signals are decomposed into various frequency or scale components. Various components are then suitably modified depending on the application at hand. In this Chapter, we will discuss mainly two types of signal decomposition techniques: transform-based decomposition and subband decomposition.
KeywordsWavelet Coefficient Finite Impulse Response Digital Filter Finite Impulse Response Filter Lena Image
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- 1.A. K. Jain, Fundamentals of Digital Image Processing, Prentice Hall, 1989.Google Scholar
- 2.E. O. Brigham, The Fast Fourier Transform, Prentice Hall, 1974.Google Scholar
- 4.P. P. Vaidyanathan, Multirate Systems and Filterbanks, Prentice Hall, 1992.Google Scholar
- 5.C. S. Burrus, R. A. Gopinath, and H. Guo, Introduction to Wavelets and Wavelet Transforms, Prentice Hall, 1998.Google Scholar
- 7.M. K. Mandai, Wavelet Theory and Implementation, Chapter 3 of M.A.Sc Thesis, Wavelets for Image Compression, University of Ottawa, 1995 (Included in the CD).Google Scholar
- 8.R. C. Gonzalez and Richard E. Woods, Digital Image Processing, Addison Wesley, 1993.Google Scholar
- 9.B. P. Lathi, Signal Processing and Linear Systems, Berkeley Cambridge Press, 1998.Google Scholar
- 10.A. N. Akansu and R. A. Haddad, Multiresolution Signal Decomposition: Transforms, Subbands, and Wavelets, 2nd Edition, Academic Press, San Diego, 2001.Google Scholar