Papers by Keyword: Chirplet Transform

Abstract: A new idea, using chirplet as the staff to define fractal dimension, is proposed in this paper, based on self- similitude of knowing essence of things from collectivity to part, from macroscopy to microcosm, in fractal theory and chirplet transformation. Chirplet fractal dimension is defined as the sum of high-frequency values of decomposed signals. The edge of infrared image is detected through chirplet fractal dimension, experimental results show that this new algorithm is simple and effective to detect whole contour and detail information, and is better than other traditional operators.

Abstract: In this paper, a robust image watermarking method in two-dimensional time-frequency distributions domain is proposed which is robust against geometric distortion. This watermarking is detected by a linear frequency change. The chirplet transformation is used to detect the watermark. The chirp signals are used as watermarks and this type of signals is resistant to all stationary filtering methods and exhibits geometrical symmetry. In the two-dimensional Radon-Wigner transformation domain, the chirp signals used as watermarks change only its position in space/spatial-frequency distribution, after applying linear geometrical attack, such as scale rotation and cropping. But the two-dimensional Radon-Wigner transformation needs too much difficult computing. So the image is put into a series of 1D signal by choosing scalable local time windows. The watermark embedded in the chirplet transformation domain. The watermark thus generated is invisible and performs well in StirMark test and is robust to geometrical attacks. Compared with other watermarking algorithms, this algorithm is more robust, especially against geometric distortion, while having excellent frequency properties.