Matrix class

The data has to be linear in memory for the VECLIB library, thus this has been done and it used in some other functions to speed them up (see the constructor how this is done).

If the VECLIB library is not used, (slower) internal functions for FFT and matrix multiplication are used. If you like to use your own FFT, only the function four1d has to be changed since the 2d function call this one sequentially.

If the LAPACK library is not used, (slower) internal functions for cholesky are used.

The matrix class is used as a container class for (part of) the images. It has not been defined as a class 'radarimage' because in that case it would have been difficult to perform operations on the images if they didn't fit in the memory as a whole. However, it might be a good idea to define functions such as phasefilter for the matrix class. This would result in calls like:

matrix < complex<real4> > BUFFERMASTER; // Container for (i=0; i<NUMBUFFERS; ++i) { // Read in phase image BUFFERMASTER.readfromfile(filename,windowsize,formatflag); // filter this buffer BUFFERMASTER.phasefilter(parameters); // Write to \outputfile BUFFERMASTER.writetofile(filename2,formatflag); }

which seems very readable and maintainable (only the member function "phasefilter" of the matrix class has to be changed if something has to be added).

If you do not have access to LAPACK, but you have a different library, we advice you to use that one. The Cholesky factorization as implemented internally has not been optimized in any way. The same holds for the VECLIB library, particularly the FFT routines. We have included the code for a Cooley-Turkey algorithm, but it handles the data quite slowly, compared to an optimized library.