Infrared Video Enhancement Using Contrast Limited Adaptive Histogram Equalization and Fuzzy Logic | ||||
| Menoufia Journal of Electronic Engineering Research | ||||
| Article 63, Volume 28, ICEEM2019-Special Issue, 2019, Page 231-236 | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/mjeer.2019.77373 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
| Aya M. gamal1; H. I. Ashiba2; Ghada ElBanby3; Adel S. Elfishawy1; Nabil A. Ismail4; Fathi E. Abd El-Samie1 | ||||
| 1Electronics & Communication Dept. Faculty of Eletronic Engineering, Menoufia University Egypt | ||||
| 2Electronics & Communication Dept. Faculty of Shoubra Engineering, BanhaUniversity Egypt | ||||
| 3Department of Automatic Control Faculty of Eletronic Engineering, Menoufia University Egypt | ||||
| 4Computer Science & Engineering Dept. Faculty of Eletronic Engineering, Menoufia University Egypt | ||||
| Abstract | ||||
| Infrared image enhancement is a challenging task due to several factors such as low dynamic range, noise and non-uniformity effect. The non-uniformity is a time-dependent noise that appears owing to the lack of sensor equalization. This paper presents two proposed approaches for infrared video enhancement. The first proposed approach depends on histogram matching. The second one depends on contrast limited adaptive histogram equalization (CLAHE) and fuzzy logic. The performance metrics of average gradient, entropy, contrast improvement factor and Sobel edge magnitude are used for evaluating the obtained results. | ||||
| Keywords | ||||
| IR video enhancement; Histogram matching; Fuzzy Logic; and CLAHE | ||||
| References | ||||
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