A Region-Based Image Enhancement Algorithm with the Grossberg Network

  • Bo Mi
  • Pengcheng Wei
  • Yong Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3972)


In order to enhance the contrast of an image, histogram equalization is wildly used. With global histogram equalization (GHE), the image is enhanced as a whole, and this may induce some areas to be overenhanced or blurred. Although local histogram equalization (LHE) acts adaptively to overcome this problem, it brings noise and artifacts to image. In this paper, a region-based enhancement algorithm is proposed, in which Grossberg network is employed to generate histogram and extract regions. Simulation results show that the image is obviously improved with the advantage of both GHE and LHE.


Grey Level Transformation Function Histogram Equalization Adaptive Weight Adaptive Histogram Equalization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Bo Mi
    • 1
  • Pengcheng Wei
    • 1
  • Yong Chen
    • 1
  1. 1.Department of Computer Science and EngineeringChongqing University ChongqingP.R. China

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