To seek a way non-invasive and adaptive to differentiate the normal and abnormal heart sound signals in order to provide more valuable reference method for clinical diagnosis. This paper made the largest Lyapunov exponent as the mainline. According to the unity of the whole signal in different stages, a method to study the characteristic in stage was proposed. First of all, we made phase space reconstitution to the typical seven normal and abnormal heart sound signals. Then, we calculated the largest Lyapunov exponents according to the phase space reconstitution parameters. At last, we compared and analyzed the mean values of the largest Lyapunov exponents. The mean value of the normal heart sound signal in S1 was 0.145, which was much larger than that of the abnormal signals and the mean value of the normal heart sound signal in S2 was larger than that of the abnormal ones, too. This conclusion means that there are chaotic characteristic in the heart sound signals and the degree of chaos in normal heart sounds is higher than that in the abnormal heart sound signals.

In this paper we present a compound anisotropic diffusion filter algorithm to apply edge sensitive ICOV operator in NCD model. According to the correlation coefficient of the ICOV operator, we obtain effective nonlinear denoising. The experiment have validated that our algorithm have better effect in smoothing and better ability in edge preservation.

Because of the limit of the optical lens’s depth, the objects of different distance usually cannot be at the same focus in the same picture, but multi-focus image fusion can obtain fusion image with all goals clear, improving the utilization rate of the image information ,which is helpful to further computer processing. According to the imaging characteristics of multi-focus image, a multi-focus image fusion algorithm based on redundant wavelet transform is proposed in this paper. For different frequency domain of redundant wavelet decomposition, the selection principle of high-frequency coefficients and low-frequency coefficients is respectively discussed .The fusion rule is that,the selection of low frequency coefficient is based on the local area energy, and the high frequency coefficient is based on local variance combining with matching threshold. As can be seen from the simulation results, the method given in the paper is a good way to retain more useful information from the source image , getting a fusion image with all goals clear.

Currently,the ultrasound image has been widely used in diagnosis and treatment of clinical medicine,the results obtained by the diagnostic accuracy and reliability of the image is directly related to the effects of diagnosis and treatment.Because ultrasound images in the imaging process inevitably contaminated noise,thus the research of inhibiting ultrasound image noise is one of the important issues in domestic and international ultrasound imaging techniques.This paper studies the multi-scale analysis and wavelet thresholding two theories,put forwarda denoising algorithm about combining the Nonsubsampling contourlet transform and a new threshold function,experiments show that the new algorithm can not only good at suppressing the noise of ultrasound images,and can better retain image edge and texture details.