scholarly journals An Adaptive Image Contrast Enhancement Technique for Low-Contrast Images

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 161584-161593 ◽  
Author(s):  
Awais Mahmood ◽  
Sajid Ali Khan ◽  
Shariq Hussain ◽  
Eslam Mohammad Almaghayreh
2019 ◽  
Vol 19 (04) ◽  
pp. 1950020
Author(s):  
Mitra Montazeri

In the image processing application, contrast enhancement is a major step. Conventional contrast enhancement methods such as Histogram Equalization (HE) do not have satisfactory results on many different low contrast images and they also cannot automatically handle different images. These problems result in specifying parameters manually to produce high contrast images. In this paper, an automatic image contrast enhancement on Memetic algorithm (MA) is proposed. In this study, simple exploiter is proposed to improve the current image contrast. The proposed method accomplishes multi goals of preserving brightness, retaining the shape features of the original histogram and controlling excessive enhancement rate, suiting for applications of consumer electronics. Simulation results shows that in terms of visual assessment, peak signal-to-noise (PSNR) and Absolute Mean Brightness Error (AMBE) the proposed method is better than the literature methods. It improves natural looking images specifically in images with high dynamic range and the output images were applicable for products of consumer electronic.


2018 ◽  
Vol 181 (22) ◽  
pp. 6-13
Author(s):  
Dominic Asamoah ◽  
Emmanuel Ofori ◽  
Stephen Opoku ◽  
Juliana Danso

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Behrouz Fathi-Vajargah ◽  
Maryam Gharehdaghi

This paper presents a novel fuzzy enhancement technique using simulated ergodic fuzzy Markov chains for low contrast brain magnetic resonance imaging (MRI). The fuzzy image contrast enhancement is proposed by weighted fuzzy expected value. The membership values are then modified to enhance the image using ergodic fuzzy Markov chains. The qualitative performance of the proposed method is compared to another method in which ergodic fuzzy Markov chains are not considered. The proposed method produces better quality image.


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