By Tamal Bose
Introducing the 1st textual content to combine the themes of electronic sign processing (DSP), electronic photo processing (DIP), and adaptive sign processing (ASP)! electronic sign and picture Processing is helping scholars enhance a well-rounded realizing of those key parts by means of concentrating on primary strategies, mathematical foundations, and complicated algorithms.
The presentation is mathematically thorough with transparent reasons, various examples, illustrations, and functions. as well as difficulties, MATLAB-based computing device tasks are assigned on the finish of every bankruptcy, making this e-book excellent for laboratory-based classes.
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Extra info for Digital Signal and Image Processing
Let x(n)be the input to a system and y(n) be the corresponding output. We will represent the output as where 8 denotes the operator that operates on the input signal. This representation will be used throughout this section. "Fromlinear systems, we know that the frequency response of a signal or system is defined as its gain and phase as a function of frequency. Chapter 1. Fundamental Concepts Linearity A system is said to be linear if it obeys the law of superposition. For inputs xl ( n ) and xz(n),let the system outputs be y l ( n ) and ~ z ( n )respectively.
The proof is straightforward and is assigned as a problem. For a stationary random process, Fact 2 simplifies to the following: In the above discussion, we assumed the availability of an ensemble of sequences or a random process. However, in practice we often have a single rehation of the random process, that is, a single sequence. In this situation, it is convenient to estimate the mean and the correlation of the random process from the single sequence. Consider a sequence ~ ( n n) ,= 0 , 1 , 2 , ..
0 0 0 0 . 17 Exponential a": (a) 0 < a < 1 (b)-1 < a < 0. I . I l 0 T . This can be done by subtracting an integer multiple of 27r from the phase. In other words, the phase is plotted as 6 f (n) modulo 2n. 1 ConsicEPr the signal The real and imaginary parts of the signal are shown in Fig. 18(a)and (b), respectively. The magnitude and phase are plotted in Fig. 18 (c) and (a). Periodic Signals Periodic signals are important because they occur often in many application areas of signal processing. As we know, periodic functions can be represented as a Fourier series, which is an inchpensable analysis tool.
Digital Signal and Image Processing by Tamal Bose