並列摘要
Due to a large amount of float-point operations are utilized, the performance achieved by adopting the traditional image enlarging methods is quite low. The problem becomes more serious for the bilinear interpolation method, which is one of the most commonly used image techniques for enlarging pictures. In the paper, we propose a novel method to reduce significantly the processing time for the enlarging techniques. The concept is quite simple, and the method is easy to implement. The float-point operations are replaced by integer operations, so the processing speed is increased. Experimental results show the superiority of the proposed method.
參考文獻
[1] M. Unser, A. Aldroubi, and M. Eden, “Enlargement or reduction of digital images with minimum loss of information,” IEEE Trans. on Image Processing, Vol. 4, pp. 247-258, Mar. 1995.
[2] K. Jensen and D. Anastassiou, “Subpixel edge localization and the interpolation of still images,” IEEE Trans. on Image Processing, Vol. 4, pp. 285-295, Mar. 1995.
[5] M. Ohira, K. Mori, K. Wada, and K. Traichi, “High quality image restoration by adaptively transformed sampling function,” IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, pp. 201-204, 1999.
[6] K. P. Hong, J. K. Paik, H. J. Kim, and C. H. Lee, “An edge-preserving image interpolation system for a digital camcorder,” IEEE Trans. Consumer Electron., Vol. 42, pp. 279-283, Aug. 1996.
[9] S. Thurnhofer and S. K. Mitra, “Edge-enhanced image zooming,” Opt. Eng., Vol 35, pp. 1862-1869, July 1996.