Numerically Lossless or Visually Lossless Wavelet Compression

I hear so very often, we need lossless image compression (meaning numerically lossless - NL). I respect the point much more when I hear it from remote sensing and photogrammetry scientists than from GIS users.

Why my differentiation? Am I diss’ing the GIS folks? I hope not, that is not my intention.

Way back in 2001 I did a little test. I was at Georgia Tech Center for GIS (CGIS) and was asked by the State of Georgia to determine what compression level was acceptable to compress the state’s Color-Infrared aerials. Wavelet NL was not available through COTS software at the time (MrSID and ECW) and CGIS was not funded to research a new compression method. We were told to research what COTS compression level to use.

So, we pulled together engineering students, business students, architectural students, geospatial scientists, and secretaries. Most had some geospatial training and a few did not. We displayed an 8-bit uncompressed image, and compressed versions of the same image at 10:1, 15:1, 20:1, 25:1 and 30:1 compressions.

The people were allowed display images side-by-side, use swipe, blend, and fade functions. They could zoom in and out, but no further than a 4x zoom.

Only one person could see the compression artifacts at a 1:1 zoom before 20:1 compression. At 20:1 all the experienced remote sensing people could see a few artifacts. The experienced GIS people could see the artifacts at a 2x zoom of 15:1, but only one of non-geospatial people (a business student) could see the artifacts at 2x 15:1. (Later she decided to work as a research assistant for me and is still in the geospatial industry).

My point is… many in the geospatial industry push the 2 – 2.5x file size saving when using NL compression; when many trained geospatial people cannot see a compression artifacts in 3-band image compressions below 10:1 unless they zoom in to 4x. (Sure, we all know of the exceptions; the remote sensing, and photogrammetry experts duly noted above; but these are the exception, not the rule.)

So why not compress at a VL level when you are not doing precise remote sensing or photogrammetry? The medical imaging industry is gravitating on between 8:1 and12:1. Is what we are doing in the geospatial world so important we have to preserve more precision than the medical imaging? Are we protecting more precision than our accuracy supports?

I for one think we are wasting space and time when we do not compress to at least the VL compression level.

A final note, I am running tests to know at what level we can wavelet compress data and not affect autocorrelation, classification, and vegetation indices. Have any of you dared such tests? Care to let us know?