Linear Motion Blur Parameter Estimation in Noisy Images Using Fuzzy Sets and Power Spectrum

• Main Authors: Moghaddam Mohsen Ebrahimi, Jamzad Mansour
• Format: Article
• Language: English
• Published: SpringerOpen 2007-01-01
• Series: EURASIP Journal on Advances in Signal Processing
• Online Access: http://asp.eurasipjournals.com/content/2007/068985

<p/> <p>Motion blur is one of the most common causes of image degradation. Restoration of such images is highly dependent on accurate estimation of motion blur parameters. To estimate these parameters, many algorithms have been proposed. These algorithms are different in their performance, time complexity, precision, and robustness in noisy environments. In this paper, we present a novel algorithm to estimate direction and length of motion blur, using Radon transform and fuzzy set concepts. The most important advantage of this algorithm is its robustness and precision in noisy images. This method was tested on a wide range of different types of standard images that were degraded with different directions (between <inline-formula><graphic file="1687-6180-2007-068985-i1.gif"/></inline-formula> and <inline-formula><graphic file="1687-6180-2007-068985-i2.gif"/></inline-formula>) and motion lengths (between <inline-formula><graphic file="1687-6180-2007-068985-i3.gif"/></inline-formula> and <inline-formula><graphic file="1687-6180-2007-068985-i4.gif"/></inline-formula> pixels). The results showed that the method works highly satisfactory for SNR <inline-formula><graphic file="1687-6180-2007-068985-i5.gif"/></inline-formula> dB and supports lower SNR compared with other algorithms.</p>