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> a common preprocessing step in computer vision (and NNs in general) is to whiten the image by standardizing or transforming pixels to a normal distribution; t

> a common preprocessing step in computer vision (and NNs in general) is to whiten the image by standardizing or transforming pixels to a normal distribution; this would tend to wipe global brightness levels, promoting invariance to illumination Is there anybody still doing this?

gwern 9y ago
Seems to still be pretty common: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C21&as_ylo=2016&q=whiten+OR+normalize+image+site%3Aarxiv.org https://scholar.google.com/scholar?hl=en&as_sdt=0%2C21&as_yl... Am I wrong?
- haeffin 9y ago
  "normalizing" is a bad search term, it can mean a lot of things. And whitening images is pretty much dead. What is done is subtracting mean colors from each pixel, but those are means over the whole database, not per-image, so that keeps brightness shifts intact.
  - gwern 9y ago
    In searches you should err on the side of broadness. If you cut it down to just 'whitening', as you can see from the snippets as well, there are plenty of hits. You may not like whitening, but it does still seem to be common.
    - haeffin 9y ago
      Using your search, at least for me, none of the snippets on the first page use normalization in the sense that you are in this context. So including that term just got you a lot of noise. And the only reference to whitening on that search page is not using it in an input pipeline, it is using ZCA to detect images that are modified to be adversarial. If you want some better data than unreliable searches, go download pretrained models for popular architectures and popular frameworks and look at the input pipelines for them. You'll find that whitening is absolutely not common for image classification/detection today (yes, there are still some cases where it is used, but typically on smaller datasets where you can't get that invariance from data, which is the way you prefer it to be - if one class actually is more likely to be present in dark images, you don't want to kill that information).
argonaut 9y ago
No, it's not widely used anymore, although I wouldn't call it rare either. The most popular image CNNs don't use them: ResNets, Inception, VGG, fully convolutional nets, etc. The Google query gwern cites is highly misleading because "normalize" in the context of neural nets for computer vision almost always means "subtract the average and then divide by the standard deviation."
deleted 9y ago
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gwern 9y ago

Seems to still be pretty common: https://scholar.google.com/scholar?hl=en&as_sdt=0%2C21&as_ylo=2016&q=whiten+OR+normalize+image+site%3Aarxiv.org https://scholar.google.com/scholar?hl=en&as_sdt=0%2C21&as_yl... Am I wrong?

haeffin 9y ago
"normalizing" is a bad search term, it can mean a lot of things. And whitening images is pretty much dead. What is done is subtracting mean colors from each pixel, but those are means over the whole database, not per-image, so that keeps brightness shifts intact.
- gwern 9y ago
  In searches you should err on the side of broadness. If you cut it down to just 'whitening', as you can see from the snippets as well, there are plenty of hits. You may not like whitening, but it does still seem to be common.
  - haeffin 9y ago
    Using your search, at least for me, none of the snippets on the first page use normalization in the sense that you are in this context. So including that term just got you a lot of noise. And the only reference to whitening on that search page is not using it in an input pipeline, it is using ZCA to detect images that are modified to be adversarial. If you want some better data than unreliable searches, go download pretrained models for popular architectures and popular frameworks and look at the input pipelines for them. You'll find that whitening is absolutely not common for image classification/detection today (yes, there are still some cases where it is used, but typically on smaller datasets where you can't get that invariance from data, which is the way you prefer it to be - if one class actually is more likely to be present in dark images, you don't want to kill that information).

argonaut 9y ago

No, it's not widely used anymore, although I wouldn't call it rare either. The most popular image CNNs don't use them: ResNets, Inception, VGG, fully convolutional nets, etc. The Google query gwern cites is highly misleading because "normalize" in the context of neural nets for computer vision almost always means "subtract the average and then divide by the standard deviation."

deleted 9y ago

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