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When shooting videos while holding the camera, motion blur from camera shake is a significant problem. Video-based approaches, as opposed to single-image deblurring, may make extensive use of information between neighboring frames. Therefore, aligning adjacent frames is one of the best methods. However, image alignment is a computationally expensive and delicate process; therefore, algorithms that aggregate information must be able to distinguish between areas that have successfully aligned and those that have not, a task that demands a high level of scene knowledge. The approach for removing motion blur from the video is suggested in this work using a histogram of Oriented Gradients (HOG) features. By evaluating the video frame quality using the four performance measures PSNR, SSIM, MSE, and RMSE, it is validated. On a Xilinx Virtex 7 VX485T, the planned work was implemented.
Keywords:
FPGA, Video Deblurring, fragile, Histogram of Oriented Gradients
Cite Article:
"Histogram-Oriented Gradients Based Video Deblurring on FPGA ", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2455-2631, Vol.7, Issue 12, page no.292 - 300, December-2022, Available :http://www.ijrti.org/papers/IJRTI2212039.pdf
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000205366
ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator