Abstract: In order to improve the visual effect of AR live video detail texture, an adaptive enhancement algorithm based on approximate matching is proposed. According to the local self-similarity of the original image, the best matching block of the initial super-resolution image block is obtained. After extracting its high-frequency information, the improved singular value decomposition (SVD) is used to embed the watermark into the original super-resolution gray image; And through the watermark extraction and reconstruction matrix, the effective high-frequency detail texture information is obtained, then the final super-resolution image is obtained, and the AR live video detail texture enhancement is completed. The experimental results show that the peak signal-to-noise ratio, structure similarity and feature similarity of the algorithm are high, and the reconstruction effect is good; After detail texture enhancement, the detail texture clarity and edge sharpness of AR live picture are better, and the best visual effect is achieved.

Panpan Yang, Lingfei Ma, Chao Yin and Yang Ping, “An Adaptive Texture Enhancement Algorithm for AR Live Screen Based on Approximate Matching” International Journal of Advanced Computer Science and Applications(IJACSA), 13(12), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0131281

@article{Yang2022,
title = {An Adaptive Texture Enhancement Algorithm for AR Live Screen Based on Approximate Matching},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0131281},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0131281},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {12},
author = {Panpan Yang and Lingfei Ma and Chao Yin and Yang Ping}
}