Peter_S
Peter_S
Hi!
I need to enlarge an Imacon 848 scan from 135 film to 140cm width. The film used is Tri-X, so quite grainy. What would in your experience be the best software and method?
I am trying Topaz Gigapixel as we speak, and seeing how Photoshop compares. The crux is keeping the grain "nice".
Any suggestions?
Thank you,
Peter
I need to enlarge an Imacon 848 scan from 135 film to 140cm width. The film used is Tri-X, so quite grainy. What would in your experience be the best software and method?
I am trying Topaz Gigapixel as we speak, and seeing how Photoshop compares. The crux is keeping the grain "nice".
Any suggestions?
Thank you,
Peter
dourbalistar
Buy more film
I haven't actually watched the video myself, but I did see this in my YouTube feed last week, maybe it has some useful information for you:
https://www.youtube.com/watch?v=ZANwdpKWxKE
https://www.youtube.com/watch?v=ZANwdpKWxKE
Particular
a.k.a. CNNY, disassembler
If you scanned it on the imacon full resolution, you should have about 148dpi in your print. In my experience that is enough, in the sense that the print will not fall apart from digital noise. The grain will likely be quite large, so any sharpening will likely make the grain more pronounced, but will not bring out more detail from the image. It will have an effect like 'clarity' in Lightroom. I would try photoshops different upres methods, and play with sharpening and print out details at 100% of your final print. You will figure out what looks best for your image. Don't trust what it looks like on the screen.
hap
Well-known
Please post examples or at least opinions of Gigapixel and PS.
willie_901
Mentor
Honestly, without knowing the intended/anticipated viewing distance, it is difficult to answer this question.
There are two aspects to increasing print size when the original pixels per inch for a digital file is low. One is optimizing the input (digital source file) and the other optimizing the output data for the printer and media .
One aspect of input optimization minimizes artifacts caused by using discrete data to model analog information. Three types of errors affect this process.
o Intensity quantization - Not enough intensity resolution
o Spatial aliasing - Not enough spatial resolution
o Temporal aliasing - Not enough temporal resolution; this applies to display monitors only
Post-production software addresses these issues.
Spatial aliasing artifacts are minimized by capture sharpening. Creative sharpening involves selective, local adjustments to optimize perceived image aesthetics. Output sharpening optimizes the file for a specific printer/paper combination.
Intensity resolution is addressed by making estimates about information we did not collect. Since we can't create information (image detail) out of nothing, all software uses models to guess about the information we wish we had. Algorithms add image intensity estimates for samples (pixels) in-between samples that contain data.
In all cases the errors are distributed among the pixels. More sophisticated software offers more flexibility in error distribution strategies.
The optimum model for estimating the missing information will be different for different situations.
For an empty region of blue sky or even a sky with clouds the modeled information is very similar to the actual (but missing) information. However, if there is a squadron of aircraft flying in formation, modeling the missing - but desired information - in that region region becomes tricky.
In your case it sounds like retaining the perceived aesthetics of film grain rendering is a priority. In other words, the information content of the original data is low. This should make the job easier.
Most of the methods and tutorials assume the original, sparse data is digital. But your original information is analog.
Assuming the image scan was optimized for a grainy negative, the issue isn't estimating missing intensity detail samples out of nothing. The detail level in a grainy negative is low (in terms of intensity quantization). The issue is modeling the perceived aesthetics of the image grain for the missing samples.
Finally printers use proprietary software drivers to increase output samples (pixels) to achieve a desired DPI. The optimum parameters depend on the printer hardware, the ink (if ink is used) and output media. Often it is best to let the printer decide how to add pixels once the input file artifacts are minimized. I have used test strips to save time and money. You may find a some increase in input file PPI works well with the printer driver's automated increase in DPI.
There are two aspects to increasing print size when the original pixels per inch for a digital file is low. One is optimizing the input (digital source file) and the other optimizing the output data for the printer and media .
One aspect of input optimization minimizes artifacts caused by using discrete data to model analog information. Three types of errors affect this process.
o Intensity quantization - Not enough intensity resolution
o Spatial aliasing - Not enough spatial resolution
o Temporal aliasing - Not enough temporal resolution; this applies to display monitors only
Post-production software addresses these issues.
Spatial aliasing artifacts are minimized by capture sharpening. Creative sharpening involves selective, local adjustments to optimize perceived image aesthetics. Output sharpening optimizes the file for a specific printer/paper combination.
Intensity resolution is addressed by making estimates about information we did not collect. Since we can't create information (image detail) out of nothing, all software uses models to guess about the information we wish we had. Algorithms add image intensity estimates for samples (pixels) in-between samples that contain data.
In all cases the errors are distributed among the pixels. More sophisticated software offers more flexibility in error distribution strategies.
The optimum model for estimating the missing information will be different for different situations.
For an empty region of blue sky or even a sky with clouds the modeled information is very similar to the actual (but missing) information. However, if there is a squadron of aircraft flying in formation, modeling the missing - but desired information - in that region region becomes tricky.
In your case it sounds like retaining the perceived aesthetics of film grain rendering is a priority. In other words, the information content of the original data is low. This should make the job easier.
Most of the methods and tutorials assume the original, sparse data is digital. But your original information is analog.
Assuming the image scan was optimized for a grainy negative, the issue isn't estimating missing intensity detail samples out of nothing. The detail level in a grainy negative is low (in terms of intensity quantization). The issue is modeling the perceived aesthetics of the image grain for the missing samples.
Finally printers use proprietary software drivers to increase output samples (pixels) to achieve a desired DPI. The optimum parameters depend on the printer hardware, the ink (if ink is used) and output media. Often it is best to let the printer decide how to add pixels once the input file artifacts are minimized. I have used test strips to save time and money. You may find a some increase in input file PPI works well with the printer driver's automated increase in DPI.