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Single parameter Image local contrast enhancement using undecimated wavelet transform

Publish Year: 1403
Type: Conference paper
Language: English
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DSAI01_012

Index date: 23 June 2024

Single parameter Image local contrast enhancement using undecimated wavelet transform abstract

Image local contrast enhancement is an important part of image quality improvement. Recently, a local contrast enhancement method based on undecimated wavelet transform was proposed, in which the detail coefficients during the 4-level reconstruction process were weighted by a Gaussian function to increase the representation of edges with low contrast. We propose an improved variant where we reduce the number of parameters from 8 to 1 by automating the selection of variance of Gaussians and making their gains dependent on a single parameter which is controlled by the user effectively resulting in one parameter which controls the intensity of local contrast enhancement. The method was tested on different images and various image quality and image contrast metrics were utilized to assess the performance. Experimental results demonstrate that our method achieves higher performance in some image quality criteria compared to conventional local contrast enhancement methods: unsharp masking and multiscale retinex. The code and demo of this implementation are available at: https://github.com/salehrayan/SP-WLCE-local-contrast-enhancement.

Single parameter Image local contrast enhancement using undecimated wavelet transform Keywords:

Single parameter Image local contrast enhancement using undecimated wavelet transform authors

Mohammad Saleh Rayani

Internet of Things Laboratory, ICT Research Institute, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf university, Bushehr, Iran- Department of Electrical Engineering, Faculty of Intelligent Systems Engineering and Data Science,

Ahmad Keshavarz

Department of Electrical Engineering, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, Iran

Mojtaba Mansorinejad

Department of Electrical Engineering, Faculty of Intelligent Systems Engineering and Data Science, Persian Gulf University, Bushehr, Iran