Hey arun-siara.
Just wanted to point out something that could be expanded on or mentioned when it comes to compression and that is the idea of a basis.
Most compression algorithms (particulary the lossy ones - but lossless ones do in one form or another) work by utilizing a basis that has represents the same information density but in a better way.
For example - images and movies like those based on JPEG or MPEG use bases based on the cosine transforms, wavelet transforms, Fourier transforms and other transforms. Each transform has its own basis and what tends to happen is that you retain so many coefficients for given basis vectors that contribute to most of the information density that is being described.
Even though chopping things off is how a lot of lossy algorithms do things, lossless methods also use their own basis. The difference between the two is that they retain all coefficients for all basis vectors that span the space and keep its dimension - so they aren't projections onto sub-spaces but a reconstruction of the information in some space.
If you can think about how the basis are represented and the context of that basis then it will help you relate the different techniques and also make sense of why they work and do the things they do in the way they do.
Just a couple of thoughts.