  Data compression techniques are characterized by four key performance indices
which are (i) associated accuracy, (ii) compression ratio, (iii) computational
work, and (iv) degree of freedom. The method of data compression developed in
this paper allows us to substantially improve all the four issues above. The
proposed transform $F$ is presented in the form of a sum with $p-1$ terms,
$F_1,..., F_{p-1}$, where each term is a particular sub-transform presented by
a first degree polynomial. For $j=1,\ldots,p-1$, each sub-transform $F_{j}$ is
determined from interpolation-like conditions. This device provides the
transform flexibility to incorporate variation of observed data and leads to
performance improvement. The transform $F$ has two degrees of freedom, the
number of sub-transforms and associated compression ratio associated with each
sub-transform $F_{j}$.
