Contrast Enhancement Technique using Discrete Wavelet Transform with Just Noticeable Difference Model for 3D Stereoscopic Degraded Video
Bhagya H K1, Keshaveni N2
1Bhagya H K, Department of Electronics and Communication Engineering, Sullia, and Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India.
2Keshaveni N, Department of Electronics and Communication Engineering, Sullia, and Affiliated to Visvesvaraya Technological University, Belagavi, Karnataka, India.
Manuscript received on December 17, 2020. | Revised Manuscript received on January 05, 2020. | Manuscript published on January 10, 2021. | PP: 7-13 | Volume-10 Issue-3, January 2021 | Retrieval Number: 100.1/ijitee.C83430110321| DOI: 10.35940/ijitee.C8343.0110321
Open Access | Ethics and Policies | Cite | Mendeley
© 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 Video Technologies for Medical, cultural, and social activities prefer 3D visual data rendering and processing. So 3D videos are captured by any capturing devices, like the digital cameras are not acceptable all the time due to the lack of capturing devices or indecent illumination or due to poor weather surroundings like Low light, rain, fog, mist, etc. reduces the contrast, thus the videos get degraded. 3D video contrast enhancement technique is an essential process for upgrading the quality and information content in the videos. The proposed work employs a discrete wavelet transform based enhancement technique with Jut noticeable difference model to improve the video frames and it is simple and computationally inexpensive. The application of DWT results in the Low and High-frequency sub-bands. The low-frequency components that contain the greatest amount of the information are improved using weighted threshold histogram equalization(WTHE) with the JND model algorithm while the high-frequency sub-bands are distortions and highly affected by noise. The Gaussian high pass filter is applied to each high-frequency sub-bands to remove the noise. Besides, enhancement gain control and luminance preservation are used to acquire the enhanced output video. At the end check the quality of the degraded video frame, the presented work is implemented in MATLAB 2018a and evaluated using objective parameters. Experimental results show that the proposed method can generate better and agreeable results than 2D videos.
Keywords: WTHE, Just Noticeable difference model, Discrete wavelet transform, Contrast enhancement, GHPF.
Scope of the Article: Discrete Optimization