Edge Enhancement by Noise Suppression in HSI Color Model of UAV Video with Adaptive Thresholding

UAV video often suffers from noise, blurred edges, fewer details. Quality improvement is essential by noise suppression with an enhancement of edges. Edge detection algorithms for the correct classification of an object and identification have swiftly displayed a system toward processing moving images or whatsoever portion taken from UAVs or drones. To realize it in this paper, we propose a novel algorithm based on HSI transformed domain. Meanwhile, within the paper, we compile some significant analysis within the field of edge enhancement. Relying upon a laboratory evaluation regarding specific proposed techniques for noise suppression with detection of edges and its enhancement process on the UAV video dataset, we confirmed individual contributions, plus our methods’ achievement corresponded over the existent ones. Our proposed Edge Enhancement Algorithm with an HSI color model is the first with better results to the best of our research knowledge. The hybrid algorithm’s effectiveness in dealing with noise reduction working with different videos by finding the SSI, MSE, NRMSE, SNR, PSNR reference-based parameters, and with a reference-less based score, viz. BRISQUE. Our research typically provides a plan to assess the edge with image enhancement from the application’s perspective, encouraging the reformers’ awareness to be evaluated in a particular computer vision context. Results obtained the outcome of the experiment proving that assertion.