Adaptive Image Equalization for Contrast Enhancement

Abstract

The image equalization is used in this paper which automatically enhanced the contrast in an input image. To model the gravy level distribution of an image the Gaussian mixture model is used. In this model to partition the dynamic range of an image into input gray level interval the Gaussian mixture modelling is used. By transforming the pixels gray level in each input interval the contrast image equalized is generated to appropriate output gray level interval. The small interval in Gaussian mixture components with larger variances, and in the mapping of input interval to the output interval gray level distribution is also used. This algorithm produces better or enhanced images then several states of an art algorithm through the experimental results. This proposed algorithm is free from parameter when compares to other form setting a dynamic range of enhanced image and for wide range also it can be applied for different types of images.

Authors and Affiliations

M M Raghavendra, S Fareed Mirza, P Harsha Vardhan

Keywords

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  • EP ID EP23640
  • DOI http://doi.org/10.22214/ijraset.2017.3180
  • Views 318
  • Downloads 5

How To Cite

M M Raghavendra, S Fareed Mirza, P Harsha Vardhan (2017). Adaptive Image Equalization for Contrast Enhancement. International Journal for Research in Applied Science and Engineering Technology (IJRASET), 5(3), -. https://europub.co.uk/articles/-A-23640