Effective Image Expansion Using Subband Filterbanks

In a wide range of image processing applications digital images available in a certain resolution level have to be expanded to larger dimensions. This expansion is required to obey certain constraints related to the smoothness of the produced image, the similarity of the latter to an original continuous space image and the complexity of the employed expansion algorithm.

[1]  M. Carter Computer graphics: Principles and practice , 1997 .

[2]  Dan E. Dudgeon,et al.  Multidimensional Digital Signal Processing , 1983 .

[3]  Jelena Kovacevic,et al.  Wavelets and Subband Coding , 2013, Prentice Hall Signal Processing Series.

[4]  Ken D. Sauer,et al.  A generalized Gaussian image model for edge-preserving MAP estimation , 1993, IEEE Trans. Image Process..

[5]  Hsieh Hou,et al.  Cubic splines for image interpolation and digital filtering , 1978 .

[6]  Anastasios N. Venetsanopoulos,et al.  Image interpolation based on variational principles , 1991, Signal Process..

[7]  Robert L. Stevenson,et al.  A Bayesian approach to image expansion for improved definitio , 1994, IEEE Trans. Image Process..

[8]  J. A. Parker,et al.  Comparison of Interpolating Methods for Image Resampling , 1983, IEEE Transactions on Medical Imaging.

[9]  Robert L. Stevenson,et al.  Improved definition image expansion , 1992, [Proceedings] ICASSP-92: 1992 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[10]  A. N. Tikhonov,et al.  Solutions of ill-posed problems , 1977 .

[11]  Edward J. Delp,et al.  Discontinuity preserving regularization of inverse visual problems , 1994, IEEE Trans. Syst. Man Cybern..

[12]  Donald Geman,et al.  Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.