Hybrid Digital Image Classification Based on Blur Detection

Authors

  • Paramjeet 1M.Tech Student, Deptt. of Electronics & Communication Engineering, I.I.E.T., Kinana, Jind, Haryana, India
  • Amit Mahal Head of Department (H.O.D.), Electronics & Communication Engineering, I.I.E.T., Kinana, Jind, Haryana, India

Keywords:

Blur detection, Feature vector, restoration, segmentation, Image enha`ncement

Abstract

Popular entertainment and communication services of internet or mobile applications is multimedia content such as image, audio and video that may suffer from low quality problem. Blur is the one of the factors that degrades the quality of image or frames in video. Enhancement or restoration of blurred image requires detection of blurred region or kernel. Therefore, blur detection is the initial and main step of blur phenomena followed by blur classification and restoration process. In this paper, we presented overview on a few defocus and motion blur detection methods with their applications. Some of this methods based on features of blurred kernel while others not. These methods can be either direct or indirect. Direct methods only identify the blurred region and segment it from un-blurred one. While indirect methods first detect and then restore the blurred region. We discussed both type of blur detection methods.

References

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Published

30-06-2017

How to Cite

Paramjeet, & Amit Mahal. (2017). Hybrid Digital Image Classification Based on Blur Detection. International Journal for Research Publication and Seminar, 8(6), 1–6. Retrieved from https://jrps.shodhsagar.com/index.php/j/article/view/1144

Issue

Vol. 8 No. 6 (2017): Apr - June 2017

Section

Original Research Article

License

Copyright (c) 2017 International Journal for Research Publication and Seminar

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