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- W4313444023 abstract "Video denoising for raw image has always been the difficulty of camera image processing. On the one hand, image denoising performance largely determines the image quality; moreover, denoising effect in raw image will affect the accuracy of the following operations of ISP processing flow. On the other hand, compared with image, video has motion information in time sequence; thus, motion estimation which is complex and computationally expensive is needed in video denoising. In view of the above problems, this paper proposes a video denoising algorithm for raw image, performing multiple cascading processing stages on raw-RGB image based on convolutional neural network, and carries out implicit motion estimation in the network. The denoising performance is far superior to that of traditional algorithms with minimal computation and bandwidth, and has computational advantages compared with most deep learning algorithms." @default.
- W4313444023 created "2023-01-06" @default.
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- W4313444023 date "2023-01-01" @default.
- W4313444023 modified "2023-10-18" @default.
- W4313444023 title "A Multi-scale Video Denoising Algorithm for Raw Image" @default.
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- W4313444023 doi "https://doi.org/10.1007/978-981-19-7184-6_28" @default.
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