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Erschienen in:
2019 | OriginalPaper | Buchkapitel
2. Windowed Fourier Transform
verfasst von : Dengsheng Zhang
Erschienen in: Fundamentals of Image Data Mining
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Abstract
This chapter presents the time–frequency analysis theory by introducing two variants of Fourier transform, i.e., short-time Fourier transform and Gabor filters. The chapter first analyzes the limitation of FT in capturing time and spatial info from a signal or image. It then introduces a naïve windowed FT or STFT to overcome the limitation. A more powerful Gaussian windowed FT or Gabor transform is then introduced to further improve FT’s capability. Difference between FT and windowed FT is discussed with illustrations. By understanding how STFT and Gabor filters work, readers are prepared for the more advanced and powerful contemporary wavelet theories.