44results about How to "Preserve image detail" patented technology

The invention discloses an SAR image noise suppression method based on a direction wave domain mixture Gaussian model, belonging to the field of image processing, mainly solving the problems of fuzzy distortion of an SAR image caused by the current denoising method and improvement of excessive zero values added by coset decomposition of direction wave, and comprising the following steps: (1) carrying out cartoon texture model decomposition on the SAR image; (2) carrying out improved direction wave transformation on the texture part; (3) carrying out fitting of the mixture Gaussian model on the high frequency subband coefficient of the coset; (4) estimating noise variance; (5) estimating noise-free coefficient by Bayesian Minimum Mean-Square Error (MMSE); (6) carrying out improved direction wave inverse transformation on the noise-free coefficient to obtain the denoised texture part; and (7) adding the cartoon part and the denoised texture part to obtain a denoised SAR image. The SAR image noise suppression method has the advantages of improved definition, better maintenance of detail information and smoother uniform region of the denoised SAR image and can be used in filtering speckle noise in the SAR image.

The invention relates to an ultrasonic medical image speckle noise inhibition method based on multi-scale anisotropic diffusion, belonging to the ultrasonic medical image noise inhibition method and aiming to solve the problems that the image edge and the image noise are difficult to distinguish by taking the gradient as the edge detection operator when the existing anisotropic diffusion technology is applied to the ultrasonic image. The ultrasonic medical image speckle noise inhibition method based on multi-scale anisotropic diffusion comprises the following steps: (1) carrying out wavelet decomposition on the image, and calculating standard model values; (2) if the first iteration is carried out, estimating the distribution parameters of the standard model values, and otherwise, executing the step (4); (3) classifying to obtain noise smoothing areas under all scales; (4) determining diffusion thresholds by using the mean value of the standard model values of a noise area, and substituting the diffusion thresholds for diffusion functions to obtain diffusion parameters; (5) weighting wavelet coefficients by using the diffusion parameters, and carrying out inverse wavelet transform; and (6) comparing diffusion thresholds in adjacent two-time iterations, and judging whether to stop. The image is processed under multiple scales, thus the result is more accurate. The ultrasonic medical image speckle noise inhibition method based on multi-scale anisotropic diffusion can be widely applied to various occasions needing to process the ultrasonic images.

The invention discloses a Contourlet domain image denoising method based on Treelet, mainly solving the problem of poor denoising effect of the existing denoising method. The Contourlet domain image denoising method comprises the implementation steps of: (1) solving a residual variable matrix by a noise-containing image NI; (2) carrying out non-local mean prefiltering on the NI and obtaining a filtered image LI; (3) carrying out translation on the LI to obtain an image PI after translation, and carrying out Contourlet decomposition on the PI; (4) carrying out denoising respectively on all decomposed high-frequency subbands, carrying out Contourlet inverse transformation on the denoised subbands and obtaining a denoised image FI; (5) carrying out inverse translation on the FI and obtaininga denoised image; and (6) repeating the steps (3)-(5) for eight times to denoise and averaging, and outputting the eight denoised images. The Contourlet domain image denoising method can effectively remove the noise in natural images containing Gaussian white noise, and can be used for change detection and image preprocessing in target identification.