Image spatial transformation in DCT domain

In this paper, we report work on generalizing spatial relationships between the DCTs of any block and its sub-blocks, which paves the way for image processing in the JPEG compressed domain. The results reveal that DCT coefficients of any block can be directly obtained from the DCT coefficients of its sub-blocks and the inter-block relationship remains to be linear. Due to the fact that the corresponding coefficient matrix of linear combination is sparse, the computational complexity of the proposed algorithms is significantly lower than that of the existing methods.

[1]  Bo Shen,et al.  Direct feature extraction from compressed images , 1996, Electronic Imaging.

[2]  Athanassios N. Skodras Direct transform to transform computation , 1999, IEEE Signal Processing Letters.

[3]  John E. Hershey,et al.  Feature cueing in the discrete cosine transform domain , 1994, J. Electronic Imaging.

[4]  Josef Kittler,et al.  On local linear transform and Gabor filter representation of texture , 1992, Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. III. Conference C: Image, Speech and Signal Analysis,.

[5]  Tore Fjällbrant,et al.  A direct computation of DCT coefficients for a signal block taken from two adjacent blocks , 1991, IEEE Trans. Signal Process..

[6]  Robert Reeves,et al.  Texture characterization of compressed aerial images using DCT coefficients , 1997, Electronic Imaging.

[7]  Shih-Fu Chang,et al.  Transform features for texture classification and discrimination in large image databases , 1994, Proceedings of 1st International Conference on Image Processing.

[8]  Ephraim Feig,et al.  Fast algorithms for the discrete cosine transform , 1992, IEEE Trans. Signal Process..