SPARTAN [5] is a system that takes advantage of attribute semantics and data-mining models to perform
lossy compression of massive data tables, which is based on the novel idea of exploiting predictive data correlations and prescribed error tolerances for individual attributes to construct concise and accurate Classification and Regression Tree (CaRT) models for entire columns of a table.
Given the data volume challenge we face, we should consider the wider use of more aggressive data compression techniques, such as
lossy compression, as a matter of course.
As one more option of DI
lossy compression implementation we will consider a way which is not the accepted standard, but it is often used during the work with images [10].
Lossless and
lossy compression technique is applied on ROI and non-ROI parts respectively (Kaur et al., 2011).
This kind of compression is "lossy." While most of the modern compression algorithms, including JPEG, MP3, and MPEG-4, most commonly use
lossy compression, they often also allow the user to choose the level of "loss." (8) The accompanying manuals and technical reports classify the results of the compression in various groups, which they give names like "very good" or "excellent quality" results.
Texture is encoded by
lossy compression in a way similar to minimum description length (MDL) principle, but here the length of the data given the model is approximated by the number of samples times the entropy of the model.
However unlike PNG, WebP allows
lossy compression of images with transparency.
Conversely,
lossy compression does not allow for perfect reconstruction of the data, but has the advantage that much higher CRs can be obtained.
The video quality is influenced by two different types of distortion which arise, on the one hand, from the effects of
lossy compression introduced by the source encoding (source distortion), and on the other hand, from the lossy transmission channel (loss distortion) [1].
Data compression methods can be divided into two categories: Lossless Compression methods without losing any part of the data and
Lossy Compression methods.
Basic ideas of lossless and
lossy compression algorithms are covered.
