4 ms·

Media always distort stories. But of course this makes you wonder how come those people can grill you during interview with all questions that you can't answer

Media always distort stories. But of course this makes you wonder how come those people can grill you during interview with all questions that you can't answer seems so imbecile. Of course to design an algorithm to find a good smaller color depth that closes to original color depth is not an easy engineering issue. I guess it is this part that the reporter messed up the story and made it sounds so ridiculous to techies.

neilk 18y ago
It may not be easy but it's a well known problem. I seriously doubt they did it from scratch.
- eugenejen 18y ago
  I guess the problem to is to do it without human assistance. Do you know any related research on this area? I am actually don't know where to start. And they probably want to design the solution to integrate with google's scale nothing infrastructure.
  - neilk 18y ago
    You have to find a limited number of colors that mostly approximates the original, to the human eye. This is how every GIF encoder works. Maybe there is something about your question that I am missing? http://en.wikipedia.org/wiki/Color_quantization http://en.wikipedia.org/wiki/Color_quantization I don't know what you mean by adapting it to Google's infrastructure. I think you meant to say "shared nothing". Tile serving is perfectly suited to such an architecture already. There's no shared state across tiles, for instance.
    - eugenejen 18y ago
      I doubt naive gif encoder will do the job. in http://en.wikipedia.org/wiki/Graphics_Interchange_Format http://en.wikipedia.org/wiki/Graphics_Interchange_Format it mentions: "The algorithms used to select the palette and to perform the dithering vary widely in output quality. Additionally, dithering significantly reduces the image's compressibility and thus works contrary to GIF's main purpose." So to goal is to get the best color palette that satisfies 1. The resulting image quality is close to original image, 2. The compressed image has to be smaller than original 3. The color quantization can be automated without too much human supervision. I think the general color quantization algorithms may solve the point 1 and 3 but not necessary point 2. Never mind, I am an idiot sometime.

neilk 18y ago

It may not be easy but it's a well known problem. I seriously doubt they did it from scratch.

eugenejen 18y ago
I guess the problem to is to do it without human assistance. Do you know any related research on this area? I am actually don't know where to start. And they probably want to design the solution to integrate with google's scale nothing infrastructure.
- neilk 18y ago
  You have to find a limited number of colors that mostly approximates the original, to the human eye. This is how every GIF encoder works. Maybe there is something about your question that I am missing? http://en.wikipedia.org/wiki/Color_quantization http://en.wikipedia.org/wiki/Color_quantization I don't know what you mean by adapting it to Google's infrastructure. I think you meant to say "shared nothing". Tile serving is perfectly suited to such an architecture already. There's no shared state across tiles, for instance.
  - eugenejen 18y ago
    I doubt naive gif encoder will do the job. in http://en.wikipedia.org/wiki/Graphics_Interchange_Format http://en.wikipedia.org/wiki/Graphics_Interchange_Format it mentions: "The algorithms used to select the palette and to perform the dithering vary widely in output quality. Additionally, dithering significantly reduces the image's compressibility and thus works contrary to GIF's main purpose." So to goal is to get the best color palette that satisfies 1. The resulting image quality is close to original image, 2. The compressed image has to be smaller than original 3. The color quantization can be automated without too much human supervision. I think the general color quantization algorithms may solve the point 1 and 3 but not necessary point 2. Never mind, I am an idiot sometime.