I am working on a project for which I need to join thousands of JPEG images losslessly (I'm not talking about the Lossless JPEG/JPEG 2000/JPEG-LS formats here).
Aforementioned images have varying levels of chroma subsampling (1x1, 1x2, 2x1, 2x2), resulting in varying MCU sizes (8x8, 8x16, 16x8, 16x16 px). However, in any given set of images to be joined together, each image has identical characteristics.
For now, let's assume I only have 2 images. Image #1 (I1) is 256x256px in size and #2 (I2) is 239x256px in size. 2x2 subsampling is used such that MCU size is 16x16px. I2 thus obviously has partial MCUs at the right edge, since its width is not evenly divisible by 16. (I've read that so-called 'partial' MCUs actually contain the data for a complete MCU, but the image dimensions instruct the renderer to only display the relevant pixels and ignore/hide the extra ones.)
Looking around for tools that could help me accomplish this, I came across a modified version of JpegTran, that contains an experimental lossless crop 'n' drop (cut & paste) feature. All the other apps I encountered that support lossless JPEG editing seem to utilise IJG's (JpegTran) code, so this seemed to be the logical choice. Also, given the sheer number of images, I wanted something that could preferably be run from the command-line so that I could automate the process with a script.
Unfortunately, while everything else worked fine, it seems JpegTran truncates the partial MCUs instead of retaining them. Thus in the example above, the final joined image contains all of I1, but only 224x256px of I2. Why 224? because 239 = 14x16+15, which means there are 14 full MCUs along the width, and 1 partial MCU (just 1px short of the complete 16px). The last 15px is what is getting blanked, leading to a 495x256px image with 15px of blank (grey) pixels at the right edge. See images below (shame that imgur re-compresses them):
(left) + 
(right)
= 
As you can clearly see, the red portion (15px) of I2 has been truncated by JpegTran. If the MCUs were 8px in width, the lost portion would have been the right-most 7px of I2. Similarly, joining I3 (256x239px) *below * I1 would cause the loss of 7 or 15px, depending on the MCU height of course:
(top) + 
(bottom)
= 
Can what I am attempting even be done, or is the so-called 'lossless' JPEG crop 'n' drop only valid for images with no partial MCUs? (Maybe that is why the feature is still in an "experimental state" more than a decade after being introduced...)
Until I know for sure that it is impossible, I am not interested in suggestions for lossy joining. Avoiding any generation loss whatsoever is the sole reason why I'm breaking my head over this, else I'd have had this done and dusted ages ago. Also, I am not interested in suggestions related to switching image formats. I do not control the source of the images.
If it can be done, how? Please keep in mind that any alternate apps suggested must ideally be capable of automation, given the requirements stated above. (But given how it's unlikely I'm even going to receive a useful answer given the constraints, I would be happy with any app suggestion just as long as it actually works. I can always look into an AutoIT/AHK script or something later to automate it.)
I understand that an odd-sized final image might cause issues, so I am fully prepared to accept any solution, even if it results in blank (preferably black) padding pixels to the right/bottom. What I mean is, I don't care if I1 + I2 is 496x256px (1px padding) or even 512x256px (17px padding) in size, as long as the final image contains all the actual image data from both source images, and the entire process is lossless. Obviously the lesser the padding (if any), the better, but at this point any solution will do.
A Windows-based solution would be perfect, but a Linux-based one would be entirely acceptable (pre-compiled binaries with no external dependencies, if at all possible, instead of just code snippets). Also, freeware please, unless nothing but paid software will do the trick.
libjpeglibrary offers some low level ways to manipulate JPEG data for lossless transformations - see the documentation section titled 'Really raw data: DCT coefficients'