By Meiqing Wang, Choi-Hong Lai
Photo popularity has develop into an more and more dynamic box with new and rising civil and army purposes in defense, exploration, and robotics. Written by means of specialists in fractal-based photograph and video compression, A Concise advent to photo Processing utilizing C++ strengthens your wisdom of basics ideas in picture acquisition, conservation, processing, and manipulation, permitting you to simply practice those options in real-world problems.
The ebook offers cutting-edge photo processing technique, together with present commercial practices for picture compression, snapshot de-noising equipment in keeping with partial differential equations (PDEs), and new photograph compression equipment, corresponding to fractal photo compression and wavelet compression. It starts off with insurance of illustration, after which strikes directly to communications and processing. It concludes with discussions of processing suggestions in accordance with photo representations and changes built in previous chapters. The accompanying CD-ROM includes code for all algorithms.
Suitable as a textual content for any path on photo processing, the e-book is also used as a self-study source for researchers who want a concise and transparent view of present picture processing tools and coding examples. The authors introduce mathematical techniques with rigor appropriate for readers with a few heritage in calculus, algebra, geometry, and PDEs. All algorithms defined are illustrated with code implementation and plenty of photos examine the result of various equipment. The inclusion of C++ implementation code for every set of rules defined permits scholars and practitioners to accumulate their very own research instrument.
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Extra resources for A Concise Introduction to Image Processing using C++
One can see that, from the above formula, the instantaneous value F(w) of the signal f (t) in the frequency domain can be decomposed into the superposition of the Gabor transform component Gf (w , τ ) . One can now study the influence of local characteristics in the time domain to F(w) by setting the time τ to a specific value. 5 The Wavelet Transform The Gabor transform involves a window function that takes into account the influence of a short time interval of the frequency content of the Fourier transform of a given signal.
17 shows that the two-dimensional Fourier transform can be split into two one-dimensional Fourier transforms. 3 Properties of the Discrete Fourier Transform The discrete Fourier transform has many properties. indd 39 9/29/08 5:49:25 PM 40 < A Concise Introduction to Image Processing Using C++ listed here. 19. 21) where a and b are constants. 4 The Fast Fourier Transform The Fourier transform is a time-consuming computation. For example, the Fourier transform of an original sequence with N points has the computational complexity O(N 2).
J. S. , 1996. 6. R. Qiuqi, Digital Image Processing Science, Publishing House of Electronic Industry, Beijing, 2001 (in Chinese). 7. W. B. Pennebaker and J. L. Mitchell, JPEG: Still Image Data Compression Standard, Springer, New York, 1993. 8. M. J. Bastiaans, Gabor’s transform and Zak transform with rational oversampling, in Signal Processing VIII: Theories and Applications, Proc. EUSIPCO-96, pp. 2021–2024, ed. G. Ramponi, G. L. , Italy, 1996. 9. W. C. Land and K. Forinash, Time-frequency analysis with the continuous wavelet transform, American Journal of Physics, Vol.
A Concise Introduction to Image Processing using C++ by Meiqing Wang, Choi-Hong Lai