PSNR: 28.60SSIM: 0.8498
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Image Super-Resolution
Image Super-Resolution is a machine learning task where the goal is to increase the resolution of an image, often by a factor of 4x or more, while maintaining its content and details as much as possible. The end result is a high-resolution version of the original image. This task can be used for various applications such as improving image quality, enhancing visual detail, and increasing the accuracy of computer vision algorithms.
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PSNR: 28.33SSIM: 0.8425
PSNR: 28.70SSIM: 0.8508
PSNR: 27.89SSIM: 0.8336
PSNR: 28.43
PSNR: 26.89
PSNR: 27.08SSIM: 0.814
PSNR: 27.14SSIM: 0.8149
PSNR: 26.64SSIM: 0.8033
PSNR: 27.03SSIM: 0.8153
PSNR: 26.69SSIM: 0.8048
PSNR: 27.3SSIM: 0.818
PSNR: 28.69SSIM: 0.8512
PSNR: 28.13SSIM: 0.8392
PSNR: 26.82SSIM: 0.8087
PSNR: 27.06SSIM: 0.811
PSNR: 27.22SSIM: 0.8168
PSNR: 27.24
PSNR: 26.68SSIM: 0.8057
PSNR: 28.20SSIM: 0.8412
PSNR: 27.01
PSNR: 26.74SSIM: 0.806
PSNR: 27.23SSIM: 0.8169
PSNR: 27.02SSIM: 0.8131
PSNR: 27.45SSIM: 0.8254