CT brain lesion detection through combination of recursive sub-image histogram equalization in wavelet domain and adaptive gamma correction with weighting distribution

Computed tomography (CT) images are vital in the diagnosis of ischemic stroke. However, CT images suffer from low contrast for lesion detection. There were many contrast enhancement techniques developed, but most of the techniques are not suitable for stroke detection in CT images due to poor lesion visualization. In order to overcome the problem, this paper introduces a contrast enhancement technique with combination of Recursive Sub-image Histogram Equalization (RSHIE) based discrete wavelet transform (DWT) and adaptive gamma correction with weighting distribution (AGCWD). It is proven from experimental results that our technique has better contrast and image quality for lesion detection compared to other contrast enhancement techniques such as extreme level eliminating histogram (ELEHE) and brightness preserving bi-histogram equalization (BBHE).