Title :
Study on Image Definition Function Based on Power-spectra Analysis
Author :
Guojin, Chen ; Miaofen, Zhu ; Kesong, Zhang
Author_Institution :
Hangzhou Dianzi Univ., Hangzhou
Abstract :
The image that is in focus has the sharper edge. The edge information gotten by Fourier transform corresponds to the higher part in the frequency domain. So the value of the image power-spectra can be used to represent the image definition. This paper analyses the essential property of the image power-spectra. The study indicates that the curves of the image power-spectra are similar in spite of different image contents. The image definition function has been constructed based on the definition of the image power-spectra. And the simulation indicates that the image definition function is obvious, no-bias, single-peaked in variation, high in the ratio of signal to noise, little in the computation quantity, excellent in the focusing performance and can reflect off-focus characteristics.
Keywords :
Fourier transforms; image processing; Fourier transform; image contents; image definition function; image power-spectra; off-focus characteristics; power-spectra analysis; signal to noise ratio; Cities and towns; Computational modeling; Conferences; Focusing; Fourier transforms; Frequency domain analysis; Image analysis; Image sensors; Layout; Robot sensing systems; Image processing; auto-focusing; definition; evaluation function; power-spectra;
Conference_Titel :
Robotic and Sensors Environments, 2007. ROSE 2007. International Workshop on
Conference_Location :
Ottawa, Ont.
Print_ISBN :
978-1-4244-1526-7
Electronic_ISBN :
978-1-4244-1527-4
DOI :
10.1109/ROSE.2007.4373977
