Optimal Gamma Correction based Gaussian Unsharp Masking Framework for Enhancementof Histopathological Images

In this paper, an optimal quality enhancement approach is proposed for Haematoxylin and Eosin stained histopathology images. This objective is achieved by introducing an optimally weighted framework. It is framed by harvesting the collective benefits of cumulative distribution based gamma- corrected interim-channel and adaptively sharpened interim intensity channel. The adaptive augmentation of Gaussian filter based sharpened image and cumulative distribution based gamma correction leads to the overall image enhancement. The main intelligence is achieved here by involving on-demand, behavioral Gaussian filter to impart the associated unsharp masking. Also, the image-dependent optimally included gamma corrected channel takes care of overall illumination. In this paper, cuckoo search optimizer is employed for attaining the desired level of enhancement, by exploring the 2-D search space in an efficient manner. Comparative performance evaluation is presented in this paper, so that the outperformance of proposed approach can be underlined.