Image data compression using spectral shifting
In this research, a novel image data compression technique using spectral shifting algorithm with reordering data system (subbanding by amplitude) coupled with filters derived from Bernstein functions  will be demonstrated. The subband coding system is a powerful technique in data compression. The new approach uses Bernstein function filter banks to split data by frequency, and the frequency shifting technique with reordering data system is applied. The frequency shifting technique transforms complex curves into many simple and smooth curves. The Bernstein interpolation functions can deal very well with smooth curves compared with other interpolation or approximating functions. The spectral shifting algorithm can be used for lossy or lossless compression. In the final step, Huffman coding or arithmetic coding, or other lossless coding techniques can be used.