Project DetailsData compression denotes the task of representing information in a compact way so it can be stored and transmitted effciently. In the case of lossy-compression,
this process may discard some information so that the reconstructed data is similar enough to the original one, by compromising between accuracy and le size. Image compression has a huge importance in a world where image resolution capabilities of digital devices are constantly growing. Therefore , efficient and practical image compression algorithms are of great concern where the goal is to produce higher quality images with smaller le sizes.
JPEG2000 is currently the gold standard for image compression and just as its former version, JPEG, is based on a sparsifying transformation (analytical dictionary), by which the data is approximated by a few coefficients. On the other hand,
the K-SVD algorithm is a method that trains a dictionary to sparsely represent real image examples. Since looking for a sparsifying transform is the core of any
popular compression algorithm, this concept holds considerable potential for data compression.
