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I would not compare a fancy NN algorithm to Bicubic interpolation, even as an example. Bicubic sucks. If someone really wants to get a decent high-res upscale o

by romaniv 10y ago

I would not compare a fancy NN algorithm to Bicubic interpolation, even as an example. Bicubic sucks. If someone really wants to get a decent high-res upscale of an image via "conventional" means (like GIMP) they would probably use something like Lanczos algorithm for upscaling -> Anthropomorphic smoothing for denoise -> unnsharp mask for clarity. And that's a simple pipeline, you can go even fanciers with masks, layers and edge-detection kernels.

lotyrin 10y ago
They aren't. They compare to techniques "A+" from R. Timofte, V. De Smet, and L. Van Gool, “A+: Adjusted anchored neighborhood regression for fast super-resolution" http://www.vision.ee.ethz.ch/~timofter/ACCV2014_ID820_SUPPLEMENTARY/ http://www.vision.ee.ethz.ch/~timofter/ACCV2014_ID820_SUPPLE... and "SRCNN" C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a deep convolutional network for image super-resolution” https://arxiv.org/abs/1501.00092 https://arxiv.org/abs/1501.00092 Their result seems not to score as well in quantitative metrics (signal to noise ratio), but is faster. (And seems to have good qualitative results, in my opinion.)
- amelius 10y ago
  Indeed, I just skimmed through the paper, and the results don't seem much better than A+ and SRCNN (even worse in some instances).
  - ska 10y ago
    Yes, they aren't notably better, but they are a lot faster. Maybe useful. I really wish people wouldn't call these algorithms super-resolution, as they already had a useful meaning.
    - TTPrograms 10y ago
      I think superoscillation is a better description of the phenomena in E&M/optics.
- romaniv 10y ago
  I'm speaking about the pictures on the website OP links to. They even say "As you can see in the example below, the upsampled image looks blurry – one would hesitate to call it enhanced." It's blurry, because they use an algorithm that produces blurry images. Lanczos, for example, would produce a much sharper picture at the expense of some minor artefacts. They don't show A+ results anywhere in the blog-post at all.

by romaniv 10y ago

lotyrin 10y ago

They aren't. They compare to techniques "A+" from R. Timofte, V. De Smet, and L. Van Gool, “A+: Adjusted anchored neighborhood regression for fast super-resolution" http://www.vision.ee.ethz.ch/~timofter/ACCV2014_ID820_SUPPLEMENTARY/ http://www.vision.ee.ethz.ch/~timofter/ACCV2014_ID820_SUPPLE... and "SRCNN" C. Dong, C. C. Loy, K. He, and X. Tang, “Learning a deep convolutional network for image super-resolution” https://arxiv.org/abs/1501.00092 https://arxiv.org/abs/1501.00092 Their result seems not to score as well in quantitative metrics (signal to noise ratio), but is faster. (And seems to have good qualitative results, in my opinion.)

amelius 10y ago
Indeed, I just skimmed through the paper, and the results don't seem much better than A+ and SRCNN (even worse in some instances).
- ska 10y ago
  Yes, they aren't notably better, but they are a lot faster. Maybe useful. I really wish people wouldn't call these algorithms super-resolution, as they already had a useful meaning.
  - TTPrograms 10y ago
    I think superoscillation is a better description of the phenomena in E&M/optics.
romaniv 10y ago
I'm speaking about the pictures on the website OP links to. They even say "As you can see in the example below, the upsampled image looks blurry – one would hesitate to call it enhanced." It's blurry, because they use an algorithm that produces blurry images. Lanczos, for example, would produce a much sharper picture at the expense of some minor artefacts. They don't show A+ results anywhere in the blog-post at all.