CDF based dual transform approach for UAV video visual enhancement in RGB model

Ashish Srivastava () and Jay Prakash ()
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Ashish Srivastava: Madan Mohan Malaviya University of Technology
Jay Prakash: Madan Mohan Malaviya University of Technology

International Journal of System Assurance Engineering and Management, 2022, vol. 13, issue 5, No 33, 2559-2571

Abstract: Abstract Unavoidable noise can be seen in video and photos taken by advanced cameras mounted to UAVs due to sensors attached, height concerns, or hardware faults. Noise is a major contributor to the degradation of both video and image quality. Both color and luminance are examples of noise. With no additional noise added, the suggested algorithm’s effectiveness was verified by discovering SSI, MSE, NRMSE, SNR, and PSNR on UAV RGB color noise. This algorithm RGB model for UAV video noise reduction gives a 5.9–15.4% increase in PSNR, a 7.8–29.4% increase in SNR, and a 32–50% improvement in NRMSE compared to current state-of-the-art noise suppression methods. An algorithm with this approach is the first in UAV video processing with better results in the calculation domain of research knowledge. As a final point, we offer up an assortment of enticing goals for further investigation.

Keywords: Video denoising; Drone images; Dual-tree complex wavelet transform; Discrete cosine transform (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s13198-022-01665-7

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