article · 2014
Multiple regions based histogram equalization
Md. Moniruzzaman, Md. Shafuzzaman, Md. Foisal Hossain
Cited by 1Abstract and details only
Abstract
Image contrast enhancement is required to improve the visual appearance of the image. Histogram is an important tool for image processing. By equalizing the histogram the contrast of an image can be increased. A widely known contrast enhancement technique is histogram equalization (HE). In this paper, a histogram equalization technique has been proposed for image contrast enhancement. The input image is divided into multiple regions and each region is mapped into output region to get the equalized histogram. The proposed method is capable of preserving and maintaining the brightness and the quality of the image. The proposed method also brings out the edges which were not in the input image. Using some performance measuring tools, the proposed technique has been compared with other existing methods. From the experimental results it can be seen that the proposed technique dominates over other existing methods.
Cite this paper
Moniruzzaman, M., Shafuzzaman, M., & Hossain, M. F. (2014). Multiple regions based histogram equalization. https://doi.org/10.1109/iciev.2014.6850750
Moniruzzaman, Md., et al. “Multiple regions based histogram equalization.” vol. 5, 2014, pp. 1–6, https://doi.org/10.1109/iciev.2014.6850750.
Moniruzzaman, Md., Md. Shafuzzaman, and Md. Foisal Hossain. 2014. “Multiple regions based histogram equalization.” https://doi.org/10.1109/iciev.2014.6850750.
Moniruzzaman, M., Shafuzzaman, M. and Hossain, M.F. (2014) ‘Multiple regions based histogram equalization’. Available at: https://doi.org/10.1109/iciev.2014.6850750.
@article{moniruzzaman2014multiple,
title = {{Multiple regions based histogram equalization}},
author = {Moniruzzaman, Md. and Shafuzzaman, Md. and Hossain, Md. Foisal},
volume = {5},
pages = {1--6},
year = {2014},
doi = {10.1109/iciev.2014.6850750}
}Made from the index record. Check names, capitalisation and page numbers against the paper. Need another style? AI for Research has over 10,000.