I am looking at the problem of reducing storage space when storing multiple images together as a single bigger image. The basic intuition is that images tend to have some similarities (like those taken at the same location or around the same point of time) and can we exploit this similarity to save space.
For instance, for JPG-encoded images, the overall flow is :
Input JPG Images -> Each image converted into RGB Image Tiles -> Reorganize similar RGB tiles together -> Again transform to JPG format . Naturally, when retrieving images, we will need to reverse the process.
I just realized that JPG images are not well suited for this as they primarily work on small 8x8 macroblocks and hence similarities at a bigger scale (at tile level - each tile being some 256x256 macroblocks etc.) are not exploited by JPG encoding much.
Is there some other image encoding format besides JPG that can exploit this kind of similarity better when aggregating multiple images ? Like will this work better with PNG encoding processes for instance ?
Look at Set redundancy compression