Abstract
Nowadays, video media is gaining increasing preference by the general public, and video denoising methods are paid lots of attention. In this paper, we present a novel Spatial-temporal Adaptive Denoising Algorithm, which adaptively changing denoising strategies according to the scene change of the micro block. The proposed method automatically chooses bilateral filter for a scene changing block and temporal filter for a relatively static block. Furthermore, our method adopts a fast motion estimation algorithm, which reduces the computational cost by adaptively adjusting the searching strategy based on the texture of micro blocks. Especially, the problem of the failure of temporal filter is alleviated with the scene changing frames. Experiments demonstrate that our method achieves satisfactory visual quality and PSNR (Peak Signal Noise Ratio) improvement.
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Lei, S. (2021). A Spatial-Temporal Adaptive Video Denoising Algorithm. In: Cao, W., Ozcan, A., Xie, H., Guan, B. (eds) Computing and Data Science. CONF-CDS 2021. Communications in Computer and Information Science, vol 1513. Springer, Singapore. https://doi.org/10.1007/978-981-16-8885-0_20
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DOI: https://doi.org/10.1007/978-981-16-8885-0_20
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