#### Silly smoke and mirrors

I'm with No Duh man,

Take a 1000 files of 2k each. Store them in one big file, instant 50% saving*. Talk mumbo jumbo to world to explain it. Add a bit of deduplication and bingo...

But if they had a lossless image compression then they wouldn't be selling dedupe software, and if they had high compression video compression they wouldn't be selling dedupe software, and if they had magic compression software, they wouldn't be selling dedupe software.....

The DCT stuff is smoke and mirrors, yes we use DCT and wavelets and fractals for image compression... it's not lossless and could never be.

You understand that the DCT approach is to take a block of pixels, calculate an equation using a DCT or wavelet or some other approach. The equation takes the form of a set of term k1x, k2x^2, k3x^3, k4x^4, k5x^5, k6x^6... k-infinity

But if x is in the range 0 to 1, then on average x is 0.5, and on average x^2 is 0.25, and on average x^3 is 0.125

So k2 is less important than k1, and k3 less important than k2 and so on. So you can throw away later terms because they contribute less than the early terms.

Using k1, k2, k3 gives a good approximation to the original data when decompressed, so you throw away k4,k5.... k-infinity terms. Thus you've taken a block of pixels (e.g. 16x16 pixels) and replaced them with perhaps 32 bits of data which when shoved through the inverse DCT gives a good approximate to the original 16x16 pixel block.

By it's nature it can never be lossless (even if you had infinity DCT terms, you'd still suffer from the float rounding errors!), so their description can never match their claim and so must be smoke and mirrors.

* A 2k file takes up a 4k cluster