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Paper Title: Algorithms for Manipulating Compressed Images


Author(s): Brain C. Smith and Lawrence A. Rowe


Main Point(s):

Linear image transformations can be performed on jpeged data without fully decompressing. More specifically, only the last step of the jpeg algorithm, namely entropy encoding of the runlength encoded DCT coefficients, has to be undone. The application of scalar multiplication, scalar addition and pixelwise addition to the RLE vectors is quite straight-forward. Nice side-effects of using the undecompressed data are that in the scalar multiplication, only the non-zero values are actually multiplied, and that scalara addition only affects the first DCT coefficient. Pixelwise multiplication is more complicated but can be made fast by precomputing a sparse representation of a matrix that depends on the quantization tables that are used for the two input images and the output image. This technique is shown to yield a speedup of 100 for a dissolve operation and a speedup of 50 for a subtitle operation.

Possible Use(s):

This technique should make editing of high resolution images possible even on machines with few memory, low bus-bandwidth or a slow processor: the user designs an effect on decompressed thumbnail-versions of the data and after he or she is content with the prototype, the operation on the full-sized data is performed on the compressed data.

Extensions:

A similar technique for MPEGed data would be the most desirable extension, because this technique is obviously good for processing video. Other extensions would be to build higher level functions from the low-level linear operations and optimize them, for example by avoiding the quantization-table scaling in the intermediate steps. It would be very interesting to develop a similar technique for non-linear image processing.

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