Least-squares spline interpolation for image data compression
Michele Buscemi, Rossella Fenu, Daniel D. Giusto, Gianluca Liggi · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1996
A new interpolation algorithm for 2D data is presented that is based on the least-squares minimization and the use of splines. This interpolation technique is then integrated into a double source decomposition scheme for image data compression. First, a least-squares interpolation is implemented and applied to a uniform sampling image. Second, the splines and the analysis of the entropy allow us to reconstruct the final image. Experimental results show that the proposed image interpolation algorithm is very efficient. The major advantages of this new method over traditional block-coding techniques are the absence of the tiling effect and a more effective exploitation of interblock correlation.