By KS Thyagarajan
With crystal readability, this publication conveys the most up-tp-date ideas in electronic snapshot processing, offering either the historical past thought and the sensible functions to varied industries, corresponding to electronic cinema, video compression, and streaming media.
* examine the function of human imaginative and prescient in photograph visualization
* includes the MATLAB codes used to generate many of the figures and tables indexed within the booklet, in addition to a number of MATLAB projects
* Case reports although out illustrate the sensible program of the idea
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Additional info for Digital Image Processing with Application to Digital Cinema
1 TWO-DIMENSIONAL DISCRETE SIGNALS There are a few basic signals that are very useful in the analysis of 2-D discrete systems. Some of these signals parallel those used in one-dimensional (1-D) systems. This section defines a few basic 2-D discrete signals. A 2-D unit impulse d[m,n] is defined as Ï1, m = n = 0 d [m ,n ] = Ì Ó0, otherwise (2-1) and is shown in Figure 2-1. The impulse function is very useful in the analysis of 2-D systems, as shown in this chapter. Another useful 2-D signal is unit step function u[m,n], which is defined as Ï1, m ,n ≥ 0 u [m ,n ] = Ì .
2-10) is not satisfied, the 2-D system is said to be unstable. We desire a stable 2-D system for processing images to produce meaningful images, otherwise, we will get saturated images, which are of no use to us. 3 TWO-DIMENSIONAL DISCRETE FOURIER TRANSFORM Fourier transform is a very useful tool in the analysis and design of linear systems. Just as periodic signals are represented as an infinite sum of sinusoids of 2 Two-Dimensional Signals, Systems, and Discrete Fourier Transform 18 harmonic frequencies, an a-periodic signal can be decomposed into an integral sum of sinusoids of continuous frequencies.
2-49) k =0 Substituting for Hd(k) in the aforementioned equation, we get N -1 • ¸ j 2 pNnk ˝e ˛ k = 0 l =-• • 2pk (n - l ) ˆ ¸ Ï 1 N -1 = Â h d [l ]Ì Â expÊ j , 0 £n £ N -1 Ë ¯ ˝˛ N Ó N k =0 l =-• h [n ] = 1 N Ï Â ÌÓ Â h [l ]e d -j 2 plk N (2-50) 2 Two-Dimensional Signals, Systems, and Discrete Fourier Transform 40 Because 1 N N -1 Â expÊË j k =0 2pk (n - l ) ˆ Ï1, if l = n + mN = , ¯ ÌÓ0, otherwise N (2-51) we arrive at the expression for h[n]: • h [n ] = Â h [n + mN ], d 0 £ n £ N - 1. (2-52) m =-• The impulse response of the FIR filter derived from samples of a continuous function Hd(W) is the infinite sum of shifted impulse response hd[n].
Digital Image Processing with Application to Digital Cinema by KS Thyagarajan