Image denoising and image coding and decoding method and device including image denoising
An image coding and image technology, applied in the field of image processing, can solve the problems of storage resource consumption and high burden of denoising processing speed, so as to ensure image quality and look and feel, reduce the burden of storage resources and processing speed, and reduce noise. Effect
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Embodiment 1
[0063] This example provides a neural network-based video denoising method, including:
[0064] The pixel values of the image area to be denoised and the reconstruction prediction residual value of the image area to be denoised are input to the convolutional neural network. The specific structure of the neural network is as figure 2 shown. Use the pixel value processing subnetwork to process the pixel values of the image region to be denoised, and use the prediction residual value processing subnetwork to process the reconstruction prediction residual value of the image region to be denoised; use a mixed processing subnetwork Jointly process the output of the pixel value processing sub-network and the output of the prediction residual value processing sub-network, and each layer of the neural network of the mixed processing sub-network processes the input of the mixed processing sub-network or the output of the upper layer of the neural network of the sub-network. The o...
Embodiment 2
[0068] This example provides a neural network-based video denoising method, including:
[0069] The pixel values of the image area to be denoised and the reconstruction prediction residual value of the image area to be denoised are input to the convolutional neural network. The specific structure of the neural network is as image 3 shown. Use the pixel value processing subnetwork to process the pixel values of the image region to be denoised, and use the prediction residual value processing subnetwork to process the reconstruction prediction residual value of the image region to be denoised; use a mixed processing subnetwork Jointly process the output of the pixel value processing sub-network and the output of the prediction residual value processing sub-network, and each layer of the neural network of the mixed processing sub-network processes the input of the mixed processing sub-network or the output of the upper layer of the neural network of the sub-network. The ou...
Embodiment 3
[0073] This example provides a neural network-based video denoising method, including:
[0074] The pixel values of the image area to be denoised and the reconstruction prediction residual value of the image area to be denoised are input to the convolutional neural network. The specific structure of the neural network is as Figure 4 shown. Use the pixel value processing subnetwork to process the pixel values of the image region to be denoised, and use the prediction residual value processing subnetwork to process the reconstruction prediction residual value of the image region to be denoised; use a mixed processing subnetwork Jointly process the output of the pixel value processing sub-network and the output of the prediction residual value processing sub-network, and each layer of the neural network of the mixed processing sub-network processes the input of the mixed processing sub-network or the output of the upper layer of the neural network of the sub-network. The o...
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