Aiming at the complex background of coronary angiograms, weak contrast between the coronary arteries and the background, a new segmentation method based on transition region extraction is proposed. Firstly, the coronary arteries are extracted by using the local complexity method based on Top-hat. Then the coronary arteries are extracted again by using the local complexity method based on Gaussian filter. Finally, the segmentation image is obtained by fusing two extracted coronary arteries images. The experiments indicate that the proposed method has better performance on the small vessels extraction and background elimination. In addition, the method is valuable for diagnosis and the quantitative analysis of vessels.

In signal processing, a frequently encountered problem is harmonic retrieval in additive colored noise, especially false peaks existence in harmonic signal peaks. The purpose of this paper is to develop an efficient approach to clear the false peaks based on cross-high-order spectral QR decomposition approach. Simulation results indicate that spectral density curve is smooth without false peaks existence. The methods have better in resolving power and performance than previous MUSIC approach. Thus, this approach is ideally suited for harmonic retrieval in additive colored noise and short data conditions, and is also accurate to estimation signal parameter in hybrid colored noises.