I, too, was at Iterated Systems in its early days.
See the correction after the comment below - Good reason to be confused. Fig 2 is actually the first step in decoding.
You are missing the significance of the 64x64. The point was that the picture was split into squares that were bigger than single pixels before encoding. In this case, the regions were 8x8, so there are 64x64 of them in the original 512x512 image. If the basic elements were 1x1 pixel the linear transformation encoding would have made the encoding bigger than the original! The images illustrate some of the steps in the iterative decoding process, which always starts with single intensity blocks in the basic elements (so 64x64 blocks) but iteratively gets closer to the original, finer grained image. It looks like magic, but the fractal theory is sound. It is a lossy process, so there is no guarantee that the encoded image has both limited losses and is small in size.
I was an algorithm developer, not in sales. For sales purposes they clearly could have chosen example images that were more naturally fractal at a scale below a pixel, so blowing them up looked good. I do not know how generally good the zooming in was.
The image is captioned as "Original 512 x 512 grayscale image, with 256 gray levels for each pixel, before fractal compression.".
So, if what your saying is true the caption is wrong? Are you saying it is the first stage of decompression? That this is the input data to the decompressor?
I'm assuming therefore that the compressor actually does use a full undownsampled (not blocky) image as it's input. Or uses it as part of it's iterative compression process. Is that correct?
Good point. The caption for Figure 2 is wrong. The picture is of the first step in decompression of a 512 x 512 image. A pity you do not actually see the original that they refer to.
I think that actually the caption is "correct", and they must have simply included the wrong image, because the text says "Figure 2 shows the
original digital image of Balloon, which is of dimensions
512 pixels by 512 pixels, with 256
gray levels at each pixel."
See the correction after the comment below - Good reason to be confused. Fig 2 is actually the first step in decoding.
You are missing the significance of the 64x64. The point was that the picture was split into squares that were bigger than single pixels before encoding. In this case, the regions were 8x8, so there are 64x64 of them in the original 512x512 image. If the basic elements were 1x1 pixel the linear transformation encoding would have made the encoding bigger than the original! The images illustrate some of the steps in the iterative decoding process, which always starts with single intensity blocks in the basic elements (so 64x64 blocks) but iteratively gets closer to the original, finer grained image. It looks like magic, but the fractal theory is sound. It is a lossy process, so there is no guarantee that the encoded image has both limited losses and is small in size.
I was an algorithm developer, not in sales. For sales purposes they clearly could have chosen example images that were more naturally fractal at a scale below a pixel, so blowing them up looked good. I do not know how generally good the zooming in was.