Volume 7 Issue 1 - May 2016

  • 1. Adaptive deblurring by piecewise linear approximation of motion blur kernel

    Authors : Athira S Vijay, Nelwin Raj N R

    Pages : 369-377

    DOI : http://dx.doi.org/10.21172/1.71.052

    Keywords : Motion blurPiecewise-linear curve Kernel estimationDeblurringSimulated annealing algorithmPSF

    Abstract :

    One of the challenges in the field of photography is the motion blur. Motion blur is actually sprinkling of images, which is caused due to the relative motion of camera and scene objects, while capturing the images with long exposure time. Blurring will significantly diminish the visual quality of images. One of the solutions to reduce the blurring effect is to try to remove the blur offline. Among the deblurring processes, the estimation of blur kernel is considered as the vital step. In this paper, we present a robust estimation of adaptive deblurring using simulated annealing algorithm. The proposed algorithm provides efficient fitness for the estimation process, even in the presence of noise as well as large blurs. The experimental result shows that, the problems of low deblurring efficiency and low PSNR ratios have been efficiently overcome by using this algorithm of adaptive deblurring using simulated annealing algorithm. Also, convergence speed of the optimization algorithm is more compared to other optimization algorithms.

    Citing this Journal Article :

    Athira S Vijay, Nelwin Raj N R, "Adaptive deblurring by piecewise linear approximation of motion blur kernel", https://www.ijltet.org/journal_details.php?id=901&j_id=3068, Volume 7 Issue 1 - May 2016, 369-377, #ijltetorg