I'm planning to acquire between 50k and 200k image per day with a 50MPixels (or 68MPixels or 130MPixels) sensor; I'll be acquiring the raw data (10 or 12 or 14 bits) from the sensor through SLVS-EC and create a raw file of my own design. The raw bitrate from the sensor may go up to 75.2 Gbps.
I may have to store 50k-250k images per day (eg., 17.5TB if 250k images are 70MB-50MPixels each). I need to keep high quality images (in particular, colors must remain accurate and textures fully detailed, hence the lossless or only light loss and nothing below 10 bits per channel), and a flexibility in edition (hence the raw).
Also images will share a lot, since I may have 2-24Hz framerate at capture; also a first processing will drop (delete) between 10% and 50% of images, so a keyframe based compression may not be suitable.
Since I need to keep the storage cost as low as possible without doing too hard compression (maybe go below 30-50MB per raw image). I'm planning to allow compression within this raw file, this compression can be lossless or lightly lossy. I'm thinking about wavelet and auto learnt dictionaries (patchs and sparse coding) for the compression, but this is not a requirement.
I will not release any sdk or raw image, so there are no need or requirement on the standard and adoption side. I'll very likely use an FPGA for signal processing (up to 75.2Gbps from the sensor), since I need very high IO and fast signal processing, and the whole package will be embedded, and as compact as possible and reasonnably light (say less than 1-2kg).
About the images, it will be natural environment with natural day light; it may include shadows and sky with sun, and hence high dynamic, but also rich (high frequency) textures which must be preserved. So likely I won't add further denoising, but I want to keep the fexibility with color processing: in particular the ability to change the signal amplification and the white/black balance.
Do you have thoughts and pieces of advice about the compression strategy for this raw format ? In particular do you think video compression algorithms (eg., HEVC) could be adapted to raw bayered data ?