Obtaining Motion Blur Parameters Form The Frequency Spectrum

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Obtaining Motion Blur Parameters Form The Frequency Spectrum

Fourier transform is applied on digital images to interprets their content in terms frequency information. To illustrate, Flat areas, where the intensity is slowly changing, result in low frequencies. Rough areas, on the other hand, result in high frequencies because of the dramatic change in the intensity value. this paper discusses the impact of manipulating the frequency information of digital images and how the frequency spectrum can be used to address a real world situation.

Filtering an image in the frequency domain is usually composed of three steps. First, the Fourier transform is calculated (DCT or DFT). Then, a certain operation is performed on the frequencies (detailed below). Finally, the inverse Fourier transform is applied on the frequency information, resulting in a modified image. The simplest category of filters (also known as the ideal filters) includes the low pass filter, the high pass filter, and the band pass filter. A low pass filter attenuates high frequencies resulting in a smoothing effect. On the contrary, a high pass filter eliminates low frequencies yielding an edge enhancement effect. Lastly, a band pass filter, which is a combination of a low pass and a high pass filters, retains a mid-range of frequencies and suppresses the low and high frequencies that fall out of the range. Band pass filtering can be used to enhance edges (suppressing low frequencies) while reducing the noise at the same time (attenuating high frequencies). Filtering is mathematically simpler to implement in the frequency domain compared to convolution in the spatial domain [3].

Also, the frequency data reflects the geometrical structure and orientation of an image...

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...requency spectrum provides meaningful information that can be used with ease to address real world problems.

Works Cited
[1] Abolhassani, Hossein, Dar, Amir, and Ehsan Saeedi. Object Speed Estimation by Using Fuzzy Set. Working paper. World Academy of Science, Engineering and Technology, 2010. Print.
[2] Lin, Huei-Yung, and K Un-Jhih Li. Vehicle Speed Estimation from Single Still Images Based on M Otion Blu R A Naly Sis. Working paper. Tsukuba Science City, Japan: Conference on Machine VIsion Applications, 2005. Print.
[3] Smith, Steven W., Dr. "The Scientist and Engineer's Guide ToDigital Signal ProcessingBy Steven W. Smith, Ph.D." Fourier Image Analysis. Web. 17 Nov. 2013.
[4] Taherkhani, Ali, and J. Mohammadi. Object Speed Estimation in Frequency Domain of Single Taken Image. Working paper. Journal of Basic and Applied Scientific Research, 2013. Print.

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