Video Enhancement using Histogram Equalization with JND Model
Bhagya H.K1, Keshaveni N2
1Bhagya H.K, Associate Professor Department of EC KVGCE Sullia, DK.
2Keshaveni N, Professor, Department of EC KVGCE Sullia, DK.
Manuscript received on 03 March 2019 | Revised Manuscript received on 09 March 2019 | Manuscript published on 30 July 2019 | PP: 2506-2511 | Volume-8 Issue-2, July 2019 | Retrieval Number: A2197058119/19©BEIESP | DOI: 10.35940/ijrte.A2197.078219
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The paper presents degraded Video contrast enhancement. These videosare taken by camera phones because of the improper illumination or limitation of the capturing devices. The existing enhancement approach may either flop to produce good and distortionless Videos. They do not enhance every area of interest properly, especially in face regions. The paperpropose histogram equalization method (HE) manipulating thenoticeable in difference model of the visual system represented as in JND-HE. This will be performed for generic frame that is contrast enhancement. In addition, the said method,JND-HE method is clubbed with the exposer correctivemethod represented by JND-HE-EC for video enhancement of face region. The EC method is to adjust the illumination of the video frame in the face region and obtain suitable illumination in the background. The demonstration result shows that generic videos and faces shallproduce pleasantvideosother than existing techniques.
Keywords: Contrast Enhancement, Histogram Equalization, Low Light Video, Human Visual Perception, Exposer Correction.
Scope of the Article: Human Computer Interactions