Trigonometry-based motion blur parameter estimation algorithm. (2018)

• Record Type: Journal Article
• Authors: Gajjar, Ruchi; Zaveri, Tanish; Banerjee, Asim; Murthy, K.V.V.
• Is Part Of: International journal of image mining. Volume 3:Number 1(2018)
• Page Start: 67
• Page End: 78
• Publication Date: 2018
• Subjects: image degradation -- motion blur -- parameter estimation -- point spread function; Image processing -- Periodicals; Data mining -- Periodicals; 006.42
• Languages: English
• ISSNs: 2055-6039

Abstract

Restoration of blurred images requires information about the blurring function, which is generally unknown in practical applications. Identification of blur parameters is essential for yielding blurring function. This paper proposes a technique for estimation of motion blur parameters by formulating trigonometric relationship between the spectral lines of the motion blurred image and the blur parameters. In majority of the existing motion blur parameter estimation approaches, length of motion blur is estimated by rotating the Fourier spectrum to estimated motion angle. This requires angle estimation to be done forehand. The proposed method estimates both, length and angle simultaneously by exploring the trigonometric relation between spectral lines, thereby eliminating the need of spectrum rotation for length estimation. The proposed technique is applied on Berkeley segmentation dataset, Pascal VOC 2007 and USC-SIPI image database. The simulation results prove that the proposed method exhibit better parameter estimation performance as compared to existing state-of-the-art techniques.