Image contrast enhancement using triple clipped dynamic histogram equalisation based on standard deviation. Issue 7 (29th April 2019)

• Record Type: Journal Article
• Authors: Zarie, Majid; Pourmohammad, Ali; Hajghassem, Hassan
• Is Part Of: IET image processing. Volume 13:Issue 7(2019)
• Page Start: 1081
• Page End: 1089
• Publication Date: 2019-04-29
• Subjects: entropy -- image enhancement -- brightness -- equalisers; standard deviation -- input image -- histogram clipping -- dynamic range -- sub‐histogram equalisation process -- enhancement ratio -- natural enhancement -- image contrast enhancement -- triple clipped dynamic histogram equalisation -- high brightness ranges -- robust contrast enhancement algorithm -- performance assessment -- entropy -- visual quality -- mean opinion score -- median brightness ranges -- maximum average information content; Image processing -- Periodicals; 621.36705
• DOI: 10.1049/iet-ipr.2018.5395
• Languages: English
• ISSNs: 1751-9659

Abstract

Abstract : Many histogram equalisations‐based methods have been proposed to be applied in contrast enhancement. However, a few methods that can simultaneously create a natural enhancement in images with low, median, and high brightness ranges are suggested. Here, a robust contrast enhancement algorithm, which is called triple clipped dynamic histogram equalisation based on standard deviation (TCDHE‐SD), is proposed. In the proposed method, the histogram of the input image is partitioned into three parts with approximately the same number of pixels based on the standard deviation. Then, the process of histogram clipping is performed on each sub‐histogram. After that, all histograms will be mapped to a new dynamic range by means of applying some simple calculations, and finally, the sub‐histogram equalisation process will be performed independently. This method is proposed to achieve the multiple purposes of the maximum average information content (entropy), controlling the enhancement ratio and preserving reasonable brightness. It also provides a natural enhancement by generating clear images with maximum details. The performance assessment of the proposed method in terms of entropy as well as visual quality based on the mean opinion score (MOS) indicates a significant advantage of it over the previous ones.