I have a large collection of oversampled images (family photos of varying 'sharpness' scanned at a uniformly high dpi) and would like to downsample them to optimise storage space whilst retaining detail within some reasonable threshold.
I am hoping to find (or build) a tool that can help me identify what I (a confessed layman) would call the 'natural resolution' of the scanned image.
For example a 70 year old black & white 6x4" print scanned at 600dpi might be downsampled to 253dpi and look 'sharp' (for some definition of sharp). The downsampled image might then be upsampled to 600dpi again with a deviation from the original that falls within an acceptable threshold. Downsampling the original to 252dpi then upsampling might result in too much deviation, therefore the tool may decide that 253dpi is the sweet spot for that image. Ideally the tool could determine the sweet spot without having to iteratively downsample and upsample.
There are many complications (noise, dust, sharp edges that represent the edges of the photo instead of the photo itself) so the tool may require user supervision. At the moment I'm just looking for pointers as to what techniques and terms I should be familiarising myself with. I have put many hours into googling this issue but all results are either overly simple pc mag stuff (e.g. 'always scan at X dpi') or impenetrable research papers.
Edit (clarification, 2014-01-11)
The paragraph above about downsampling then upsampling is just to illustrate my point about determining loss of detail. In my actual workflow I only intend to downsample (no subsequent upsample step). The goal is to find an algorthm that on a per-image basis will determine the lowest resolution I can downsample to without sacrificing image detail (or sacrificing within an acceptable limit).