Deblurring of Noisy or Blurred Image by Using Kernel Estimation Algorithm

Abstract

This paper presents, taking the photos under dim lighting conditions using a hand-held camera becomes blurry or noisy. If the camera is set to a long exposure time, the image is blurred due to camera shake. While, the image will be dark and noisy if it is taken with a short exposure time with a high camera gain. By combining the both information extracted from both blurred and noisy images, this paper shows how to produce a high quality image that cannot be obtained by simply denoising the noisy image or deblurring the blurred image alone. The aim of is image deblurring with the help of the noisy image. First, both images are used to estimate an accurate blur kernel from a single blurred image. Second, by using both images, a residual deconvolution is proposed to reduce ringing artifacts inherent to image convolution. Third, the remaining ringing artifacts in smooth image regions are further suppressed by a gain-controlled deconvolution process. We demonstrate the effectiveness of our approach using a number of indoor and outdoor images taken by hand-held cameras in low lighting environments with some applications.

Authors and Affiliations

Joseph Anandaraj. S, R. Deepa, C. Helen Prema

Keywords

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  • EP ID EP18813
  • DOI -
  • Views 279
  • Downloads 9

How To Cite

Joseph Anandaraj. S, R. Deepa, C. Helen Prema (2014). Deblurring of Noisy or Blurred Image by Using Kernel Estimation Algorithm. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 2(9), -. https://europub.co.uk/articles/-A-18813