How to get motion blur parameters from frequency. The Fourier transform of the frequency spectrum is applied to digital images to interpret their content in terms of frequency information. To illustrate, flat areas, where the intensity changes slowly, produce low frequencies. Rough areas, on the other hand, produce high frequencies due to the dramatic change in intensity value. This article discusses the impact of digital image frequency information manipulation and how the frequency spectrum can be used to address a real-world situation. Filtering an image in the frequency domain usually consists of three steps. First, the Fourier transform (DCT or DFT) is calculated. Then, a certain operation is performed on the frequencies (detailed below). Finally, the inverse Fourier transform is applied to the frequency information, resulting in a modified image. The simplest category of filters (also known as ideal filters) include the low pass filter, the high pass filter, and the band pass filter. A low pass filter attenuates high frequencies obtaining an attenuating effect. In contrast, a high-pass filter eliminates low frequencies producing an edge-enhancing effect. Finally, a band-pass filter, which is a combination of low-pass and high-pass filters, maintains a midrange of frequencies and suppresses low and high frequencies that fall outside the range. Bandpass filtering can be used to enhance edges (suppressing low frequencies) while reducing noise (attenuating high frequencies). Filtering is mathematically simpler to implement in the frequency domain than convolution in the spatial domain [3]. Furthermore, frequency data reflects the geometric structure and orientation of an image… in the center of the paper… the frequency spectrum provides meaningful information that can easily be used to address real-world problems. Works Cited[1] Abolhassani, Hossein, Dar, Amir and Ehsan Saeedi. Estimation of object velocity using fuzzy set. Working document. World Academy of Science, Engineering and Technology, 2010. Print.[2] Lin, Huei-Yung, and K An-Jhih Li. Vehicle speed estimation from single still images based on M Otion Blu RA Naly Sis. Working document. Tsukuba Science City, Japan: Computer Vision Applications Conference, 2005. Print.[3] Smith, Steven W., Dr. “The Scientist and Engineer's Guide to Digital Signal Processing” by Steven W. Smith, Ph.D.” Fourier Image Analysis. Network. November 17, 2013.[4] Taherkhani, Ali and J. Mohammadi. Estimation of object velocity in the frequency domain of a single image taken. Working paper. Journal of basic and applied science research, 2013. Print.