PSNR (Raw): 41.02SSIM (Raw): 0.948
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Image Denoising
Image Denoising is a computer vision task that involves removing noise from an image. Noise can be introduced into an image during acquisition or processing, and can reduce image quality and make it difficult to interpret. Image denoising techniques aim to restore an image to its original quality by reducing or removing the noise, while preserving the important features of the image.
<span style="color:grey; opacity: 0.6">( Image credit: Wide Inference Network for Image Denoising via Learning Pixel-distribution Prior )</span>
논문
PSNR (sRGB): 39.70SSIM (sRGB): 0.961
PSNR (sRGB): 40.39SSIM (sRGB): 0.964
PSNR (sRGB): 39.52SSIM (sRGB): 0.957
PSNR (sRGB): 39.47SSIM (sRGB): 0.957
SSIM (sRGB): 0.957Average PSNR: 39.50
PSNR (sRGB): 39.99SSIM (sRGB): 0.958
PSNR (sRGB): 40.35SSIM (sRGB): 0.972
PSNR (Raw): 40.92SSIM (Raw): 0.947
PSNR (sRGB): 39.72SSIM (sRGB): 0.959
PSNR (sRGB): 40.07SSIM (sRGB): 0.960
PSNR (Raw): 39.60SSIM (Raw): 0.938
PSNR (Raw): 39.34SSIM (Raw): 0.932
PSNR (sRGB): 39.96SSIM (sRGB): 0.960
PSNR (sRGB): 39.71SSIM (sRGB): 0.958
SSIM (sRGB): 0.973
PSNR (Raw): 39.44SSIM (Raw): 0.931
PSNR (sRGB): 38.71SSIM (sRGB): 0.951
PSNR (sRGB): 40.02SSIM (sRGB): 0.960
PSNR (Raw): 40.22SSIM (Raw): 0.938
PSNR (sRGB): 39.72SSIM (sRGB): 0.959
PSNR (sRGB): 40.30SSIM (sRGB): 0.961
PSNR (sRGB): 40.08SSIM (sRGB): 0.962
PSNR (sRGB): 39.46SSIM (sRGB): 0.957
PSNR (sRGB): 30.78SSIM (sRGB): 0.801
PSNR (Raw): 39.25SSIM (Raw): 0.931
PSNR (sRGB): 38.95SSIM (sRGB): 0.952
PSNR (sRGB): 39.89SSIM (sRGB): 0.960
PSNR (sRGB): 39.28SSIM (sRGB): 0.956