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.

The invention provides a method for image noise reduction processing. The method for the image noise reduction processing comprises the following steps: a directional template is established and weight deviation is calculated according to the directional template; a weight deviation mean value is calculated according to the weight deviation; a determinative factor is calculated according to the weight deviation mean value; a weight filtering mean value is calculated according to the result and output as a strengthened image. According to the technical scheme, noise reduction of the image is achieved in a self-adaptive mode through consideration of directional information and deviation information. Meanwhile, image details can be well kept, the visual effect of the image can be improved in a self-adaptive mode, so that the influence by the noise is reduced to a certain extent and the method for the image noise reduction processing and the system for the image noise reduction processing are used for the noise reduction of video images.

The invention discloses an image processing method and device, belonging to the field of image display. The invention includes an image processing method based on brightness compensation and contrast-tone adjustment, by sequentially performing brightness compensation and contrast-tone adjustment on the image to be displayed. In the present invention, the output image after compensation processing is obtained by sequentially performing brightness compensation and contrast-tone compensation on the image to be displayed, so that when the display device reduces the brightness, the output image displayed by the display device still has sufficient contrast and tone, and at the same time Guarantee the image details to the greatest extent. Therefore, it is ensured that the images displayed by the display device still have sufficient visibility when the power consumption of the display device is reduced.

The invention discloses a collocation method of a transceiving channel of an ultrasonic imaging system; for a transceiving sub-array composed of adjacent array elements, the number of the array elements of the transceiving sub-array is set to be n exponents of 2, and when n is a positive integral larger than or equal to 2, the following steps are conducted: each array element, which is positionedat the symmetrical and middle part of the transceiving sub-array and is not less than 2 and not more than n exponents of 2 minus 2 and is the integral multiple of 2, is correspondingly collocated with a receiving channel. The collocation method of the transceiving channel of the ultrasonic imaging system not only can maintain the detail of the images formed by ultrasonic echo signals and improve image quality, but also can reduce the number of channels, thus guaranteeing the image quality (resolution, penetrating power and intensity) and cost reliability at the same time.