Deep Region Adaptive Denoising for Texture Enhancement

Image denoising is a highly challenging problem yet important task in image processing. Recently, many CNN-based denoising methods have made great performances but they commonly denoise blindly texture and non-texture regions together. This frequently leads to excessive texture smoothing and detail...

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Veröffentlicht in:	IEEE access 2022, Vol.10, p.122286-122301
Hauptverfasser:	Lee, Seong-Eui, Woo, Sung-Min, Kim, Jong-Han, Ryu, Je-Ho, Kim, Jong-Ok
Format:	Artikel
Sprache:	eng
Schlagworte:	Ablation Artificial neural networks convolution neural network Convolutional neural networks Correlation cross attention Discrete cosine transform Discrete cosine transforms High frequency Image enhancement Image processing Image quality Neural networks Noise control Noise reduction Region adaptive image denoising Smoothing Task analysis texture classification texture enhancement Texture mapping Transformers
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