Overwrite child block pixel values with transform block pixel values.
For each child block apply stored transforms against specified transform block.
Use any blank starting image of same size as original image.
Read in child block and tranform block position, transform, and size information.
Store location of parent block (or transform block), affine transform components, and related child block into a file.
Upper left corner child block, very similar to upper right parent block.
Typically an affine transform is used (w*x = a*x + b) to match grayscale levels.
Calculate a grayscale transform to match intensity levels between large block and child block precisely.
Determine which larger block has the lowest difference, according to some measure, between it and the child block.
Need to reduce the size of the parent to allow the comparison to work. This software package allows you to analyze, edit, process, 8-, 16- and 32-bit images of various formats - including the DICOM format, which is especially.
Compare each child block against a subset of all possible overlapping blocks of parent block size.
Divide each parent block into 4 each blocks, or “child blocks.”.
Take a starting image and divide it into small, non-overlapping, square blocks, typically called “parent blocks”.
States that if the error difference between the target image and the transformation of that image is less than a certain value the transforms are an equivalent representation of the image.
Try and find a set of transforms that map an image onto itself.
Started with Michael Barnsley, and refined by A.
Takes advantage of similarities within an image.
Different type of compression scheme worth exploring.
Fractal Image Compression By Cabel Sholdt and Paul Zeman
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