NDLI: MFO-based thresholded and weighted histogram scheme for brightness preserving image enhancement

Content Provider	IET Digital Library
Author	Bhandari, Ashish Kumar Maurya, Shubham Meena, Ayur Kumar
Abstract	Histogram equalisation (HE) is a simple and effective image enhancement technique. However, it suffers from excessive brightness change and provides degradation in the visual aspect of the image. To overcome the shortcomings in the HE, a novel histogram framework is proposed in this study. The image histogram is first segmented into two parts using the Otsu's thresholding method. Then, both of the upper and lower histograms are constrained to control the level of enhancement. These constraint parameters are computed through moth-flame optimisation algorithm. After constraining the histograms, mean shift correction is performed to ensure there is a minimum level of mean shifting from input to output image. Traditional HE is then applied with a modified histogram to obtain mapping function for lower and upper grey level individually. This enhanced image provides a balance between the level of enhancement and preservation of the important features of the image for high-level processing. The effectiveness of the proposed method is highlighted with a detailed comparison with other closely related schemes. Through the proposed routine, the enhanced images achieve a good trade-off between features enhancement, low contrast boosting, and brightness preservation in addition to the natural feel of the original image.
Starting Page	896
Ending Page	909
Page Count	14
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 6, May (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/6
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5258
Journal	IET Image Processing
Publisher Date	2019-01-16
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Brightness Brightness Preservation Computer Vision And Image Processing Technique Effective Image Enhancement Technique Excessive Brightness Change Feature Enhancement High-level Processing Histogram Equalisation Image Enhancement Image Histogram Image Segmentation Lower Grey Level Lower Histograms Mean Shift Correction Modified Histogram Moth-flame Optimisation Algorithm Optical, Image And Video Signal Processing Optimisation Optimisation Technique Otsu's Thresholding Method Output Image Upper Grey Level Upper Histograms Visual Aspect Weighted Histogram Scheme
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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