Contrast enhancement of digital mammograms using a novel walking ant histogram equalisation
Abubacker Kaja Mohideen, Kuttiannan Thangavel · International Journal of Computational Vision and Robotics · 2015
Contrast enhancement of medical images could improve the quality of its visual contents for better diagnosis. In this paper, a novel walking ant histogram equalisation (WAHE) is proposed to improve the contrast of digital mammograms. The proposed method is hybridisation between the histogram equalisation with a novel ant colony optimisation (ACO) algorithm. Histogram equalisation is the concept of transferring input intensities to desired output intensities while improving the visual content of the images. Here we have used ACO for constructing the transfer functions. A fitness function is employed to control the transfer function construction in a balanced way. The experiments are carried out with the digital mammograms received from MIAS database, and results indicate the latent performance of the proposed contrast enhancement approach over the existing with finest results on all the contrast enhancement measures and the classification accuracy.