4 ms·

It’s like systems that add zeros (floating point math) to the right of the decimal. 18.00000 is not the same as 18. Thoughts?

etrautmann 6y ago
No - 000000 is not based on a statistical model of what’s most likely to be right if the decimal place. In natural images - the statistical structure allows for this image upscaling but without revealing any previously hidden detail - just using know statistics of the world to show what might be there.
gmfawcett 6y ago
That's not how floating point math works? At least not for standard floats (IEEE 754), and except for very large integers (near 2^m, where m is the mantissa of the FP type). Floats have an exact representation for integers within their mantissa range -- i.e., '18' is exactly the same as '18.0000'.
- Izkata 6y ago
  They're correct when it comes to scientific fields - the number of significant figures is important, so 18.0 and 18.000 really do mean different things.
  - gmfawcett 6y ago
    Sure, of course... I guess they just gave a poor example of what they were trying to express.
dejj 6y ago
You probably want go with 0.1+0.2 != 0.3
- HenryBemis 6y ago
  I would say that it's like pixel's RGB at address 1x1 is 0-0-0 and pixel at address 1x2 is 0-0-2 and squeezing between them a pixel with color 0-0-1 (averaging the two values near it)(assuming doing this on a image that has 1 pixel height and e.g. 2 pixes width; so that the new image would be would be: 1x1 0-0-0 (original) 1x2 0-0-1 (made up) 1x3 0-0-2 (original)
  - webmaven 6y ago
    What you're describing is relatively straightforward (bi)linear interpolation. It is worth noting that even at this relatively simple level, going with bicubic interpolation instead will usually give you nicer results, except in cases where the hard edges in the image are only horizontal or vertical.
genericone 6y ago
I dont think you mean for floating point, but for mechanical tolerances. Many times, you dont want to pay an extra $50,000 for the 5 digits of precision... but sometimes you do. Shitty system if it automatically messed up all your part tolerances.

etrautmann 6y ago

No - 000000 is not based on a statistical model of what’s most likely to be right if the decimal place. In natural images - the statistical structure allows for this image upscaling but without revealing any previously hidden detail - just using know statistics of the world to show what might be there.

gmfawcett 6y ago

That's not how floating point math works? At least not for standard floats (IEEE 754), and except for very large integers (near 2^m, where m is the mantissa of the FP type). Floats have an exact representation for integers within their mantissa range -- i.e., '18' is exactly the same as '18.0000'.

Izkata 6y ago
They're correct when it comes to scientific fields - the number of significant figures is important, so 18.0 and 18.000 really do mean different things.
- gmfawcett 6y ago
  Sure, of course... I guess they just gave a poor example of what they were trying to express.

dejj 6y ago

You probably want go with 0.1+0.2 != 0.3

HenryBemis 6y ago
I would say that it's like pixel's RGB at address 1x1 is 0-0-0 and pixel at address 1x2 is 0-0-2 and squeezing between them a pixel with color 0-0-1 (averaging the two values near it)(assuming doing this on a image that has 1 pixel height and e.g. 2 pixes width; so that the new image would be would be: 1x1 0-0-0 (original) 1x2 0-0-1 (made up) 1x3 0-0-2 (original)
- webmaven 6y ago
  What you're describing is relatively straightforward (bi)linear interpolation. It is worth noting that even at this relatively simple level, going with bicubic interpolation instead will usually give you nicer results, except in cases where the hard edges in the image are only horizontal or vertical.

genericone 6y ago

I dont think you mean for floating point, but for mechanical tolerances. Many times, you dont want to pay an extra $50,000 for the 5 digits of precision... but sometimes you do. Shitty system if it automatically messed up all your part tolerances.