Improving histogram-based image contrast enhancement using gray-level information histogram with application to X-ray images

Ming Zeng, Youfu Li, Qinghao Meng, Ting Yang, Jian Liu

    Research output: Journal Publications and ReviewsRGC 21 - Publication in refereed journalpeer-review

    53 Citations (Scopus)

    Abstract

    Many applications of histogram-based techniques for the purposes of image enhancement are well known. However, these techniques often fail to produce satisfactory results for a broad variety of low-contrast images (e.g., X-ray images). In this paper, we propose a new form of histogram for image contrast enhancement. The input image is first divided into several equal-sized regions according to the intensities of gradients, their corresponding statistical values of gray levels are then modified respectively, and finally the processed histogram for the whole image is obtained by the summation of all the weighted values of regions. The fundamental characteristic of this new form of histogram is that the amplitudes of its components can objectively reflect the contribution of the gray levels to the representation of image information. Accordingly, this new histogram is called gray-level information histogram. The performance of many histogram-based enhancement techniques might be improved dramatically using the proposed histogram. Testing on the X-ray images validates the effectiveness of the new histogram. © 2011 Elsevier GmbH. All rights reserved.
    Original languageEnglish
    Pages (from-to)511-520
    JournalOptik
    Volume123
    Issue number6
    DOIs
    Publication statusPublished - Mar 2012

    Research Keywords

    • Gray-level information histogram
    • Histogram equalization
    • Image enhancement
    • X-ray image

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