Examples of Image Analysis by Wavelet Transform
Taketoshi Okuno, Shigeru NISHIO, Og-Gyu Kim
Abstract
Open-access reader
Taketoshi Okuno, Shigeru NISHIO, Og-Gyu Kim
Abstract
Open-access reader
It is well known that the wavelet transform has a new possibility in data analysis on not only frequency but also time/spatial domain. Continuous wavelet transform is effective for the signal of which the frequency is changing in time, such as turbulent velocity data. This technique is applied to the visualized image here as a edge detection method. In order to analyse image data, the discrete wavelet transform must be a effective technique. New image analysing method would be derived from the relationship between the wavelet transform and the multi-resolution analysis. The maxima analysis on wavelet domain is shown as an example.
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It is well known that the wavelet transform has a new possibility in data analysis on not only frequency but also time/spatial domain. Continuous wavelet transform is effective for the signal of which the frequency is changing in time, such as turbulent velocity data. This technique is applied to the visualized image here as a edge detection method. In order to analyse image data, the discrete wavelet transform must be a effective technique. New image analysing method would be derived from the relationship between the wavelet transform and the multi-resolution analysis. The maxima analysis on wavelet domain is shown as an example.
Key concepts: Discrete wavelet transform, Wavelet transform, Wavelet, Second-generation wavelet transform, Stationary wavelet transform, Harmonic wavelet transform, Wavelet packet decomposition, Lifting scheme