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Missing: Short explanation of the image capture pipeline

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まだ誰も着手していません。

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Issue には対象となるレッスンファイルもテストも記載されていません。まず、初心者向けの画像処理レッスンを見つけ、現在の構成とライセンスに関する案内を確認してください。Issue に列挙されたトピックを含め、適切にライセンスされた図、または置き換えた図とともに、合意された短いパイプラインの説明が追加されれば完了です。

索引モデルが issue の本文から書いたものです。

説明

help wanted type:discussion

Hi all,
as a followup to todays DataCarpentry onboarding I feel like a image processing workshop aimed at beginners should contain a short description of the image processing pipeline.
Lacking any pictures myself, I will put a couple of diagrams in here, that I found using some google searches, so licensing may vary...

First We start with this overview diagram:
overview of image capture

To summarize(kind of in reverse), here we see that a rasterized image can only be captured by an imaging device, if an object is properly lighted.
To highlight the first couple of issues

  • Lighting affects the visual perception of an object. light in a particular color can only be captured if the object receives this color and actually reflects it towards the device.
  • All known devices today rasterize the image into something called pixels, which defines the lowest available resolution. The light intensity captured by this pixel therefore is the integral across the surface area of this pixel.

Moving forward to the imaging device itself, we can use a diagram like this:
in-photo-camera capture
To summarize, we see that from the outside the entire electromagnetic spectrum has to pass through the lens, optionally pass some filters in order to reach the sensor that converts photon counts to intensity levels in pictures.

This brings us to the issues that can occur in a device:

  • assuming no filtering is present, the lens system affects the picture, obviously
  • Intensity levels: there is a minimum sensitivity level and a maximum intensity in all devices that they can process. Hence a quantization procedure has to be applied, in order to transform intensities to values.
  • color rasterization: In 99.9% of all consumer devices a color pattern is used(the image shows the so-called Bayer Pattern) to generate from a single capture of photon intensities a color image. This means that adjacent pixels only have information about particular color channels, and the other channels are obtained via interpolation.

Another diagram showing the entire pipeline

Pictures from here:
[1]
[2]
And then we are at the point where a camera chooses a file format.
File Format are chosen according to enhance transferability in a certain application. If your're looking at a image gathered by an expensive microscope with a program supplied by a vendor, chances are that the vendor has a file format for this particular application. If you're looking at camera photos with your friends a file format that is portable and adapted to the human visual system, (e.g. JPEG or JPEG2000) is chosen. Diagrams are often transferred using PNG.

Things we discussed today, but that I have not touched upon here:

  • The generation of information, or the destruction of information using resizing operations.
  • Color spaces
  • psychological perception

Thanks for all your work on this episode!

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