A Novel Algorithm of Image Enhancement Based on Pulse Coupled Neural Network Time Matrix and Rough Set

  • Authors:

  • Yide Ma;Dongmei Lin;Beidou Zhang;Chunshui Xia

  • Affiliations:

  • Lanzhou University, Lanzhou, China;Lanzhou University, Lanzhou, China;Lanzhou University, Lanzhou, China;Lanzhou University, Lanzhou, China

  • Venue:
  • FSKD '07 Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 03
  • Year:
  • 2007

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Abstract

This paper describes a novel algorithm of image enhancement based on Pulse Coupled Neural Network (PCNN) time matrix and Rough Set indiscernibility relation. Firstly, detect image noise using PCNN time matrix, and then partition the original image into three sub-images according to intensity attribute and noise attribute. Secondly, denoise using filtering methods based upon PCNN. Lastly, complete sub-images and enhance each of them by different methods. For the gray images with many object details in dark regions and badly corrupted by impulse noise, the computer simulations show excellent enhancement effect. Namely, noise can be reduced efficiently, object details can be enhanced better and the image would become clear after it is processed by this algorithm. Moreover, the effect of this algorithm is better than that of traditional image enhancement algorithm. Key words: Rough Set theory; Indiscernibility relation; Pulse Coupled Neural Network; Time matrix; Image enhancement