Abstract
Image fusion technique is playing important role in image processing. The main objective of image fusion is to integrate the information from several input images into a single image. The consequence of fused image consists of more precise information when compared to any of the input images. Image fusion plays pivotal role in image reconstruction. We have developed novel algorithm and implemented to evaluate quality metrics of fused video frames. This algorithm determines the quality performance between the fused video frame and unprocessed input video frame. The focal point of this paper is evaluating quality of fused video frame using structural similarity index (SSIM) and visual information fidelity (VIF) assessment methods.
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Sai Prasad Reddy, K., Nagabhushan Raju, K., Sailaja, D. (2020). A Novel Algorithm for Quality Evaluation Metrics of Fused Live Video Frames. In: Jyothi, S., Mamatha, D., Satapathy, S., Raju, K., Favorskaya, M. (eds) Advances in Computational and Bio-Engineering. CBE 2019. Learning and Analytics in Intelligent Systems, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-030-46939-9_15
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DOI: https://doi.org/10.1007/978-3-030-46939-9_15
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