Adaptive image enhancement method using contrast limitation based on multiple layers BOHE

Abstract

Multiple layers block overlapped histogram equalization (MLBOHE) is a classic image enhancement method. However, median filter is used in it to reduce noises which cause the degeneration of the local information. Moreover, the hidden details are not revealed effectively during the image fusion processes. To solve these drawbacks, an adaptive image enhancement method using contrast limitation is proposed in this paper. Based on MLBOHE, the proposed method employs a contrast limited method to suppress noises before BOHE is performed in each layer sub-blocks. Then an improved image fusion mode is applied to adaptively merge the multilayered BOHE images. The way to obtain the fusion weights by this fusion mode is according to the entropy value of each layer sub-blocks. In addition, four Image Quality Measures (IQMs), namely peak signal-to-noise ratio (PSNR), image clarity, contrast measure (EME) and feature similarity index metric (FSIM), are used to analyze the effectiveness of the proposed method. Simulation results show that the proposed method has high performance in suppressing noises and displaying more trustworthy details. Besides, this method outperforms the existing methods in weakening the excessive enhancement for low illumination and foggy images.