This paper proposes a YUV color image super-resolution reconstruction algorithm based on sparse representation. The R, G, B components of color image are highly correlated, three-channel super-resolution independent reconstruction will lead to color distortion, so in this paper the color image is firstly converted to the Y, U, V three channels, and then super-resolution reconstruction. For choosing the regularization parameter, this paper proposes an adaptive regularization parameter method; it has a good inhibitory effect on image noise and adaptive super-resolution reconstruction of color images. The results of experiment show that the proposed algorithm has a better PSNR, compared with bicubic interpolation method and sparse representation. The adaptive super-resolution reconstruction can further improve the quality of the reconstructed image and the method is robust to image noise.
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.
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