Glicbawls - Grey Level Image Compression by Adaptive Weighted Least Squares
نویسندگان
چکیده
In recent years most research into lossless and near lossless compression of greyscale images could be characterized as belonging to either of two distinct groups The rst group which is concerned with so called practical algorithms encom passes research into methods that allow compression and decompression with low to moderate computational complexity while still obtaining impressive compression ra tios Some well known algorithms coming from this group are LOCO CALIC and P AR The other group is mainly concerned with determining what is theoretically possible Algorithms coming from this group are usually characterized by extreme computational complexity and or huge memory requirements While their practical applicability is low they generally achieve better compression than the best practical algorithm of the same time thus proving beyond a doubt that the practical algorithms fail to exploit some redundancy inherent in the images Well known examples are UCM and TMW
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Paper Title (use style: paper title)
In the paper ultimately efficient image lossless coding methods are described. They are based on least-squares adaptive prediction, possibly combined with normalized LMS algorithm. Their performance is comparable to that of TMW, and MRP 0.5 techniques, while their computational complexities are smaller than those for the two reference methods. The new algorithms are supported by an advanced ada...
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