Adaptive gray-level image pseudo-color processing method

Abstract

The present invention discloses an adaptive gray-level image pseudo-color processing method. The method comprises: performing statistics of the gray value of a gray-level image, and obtaining the appearance probability distribution of each gray value in the image; expanding the image in the dynamic range of the gray value from 0 to 255, and obtaining the gray value balance histogram of the image; selecting three most obvious peak values in the gray value balance histogram, and respectively taking the three peak values as the mean values of the three-color (red, green and blue) Gaussian channels; determining the variance of the Gaussian channels according to the distribution of the three peaks, distributing the weights for the Gaussian channels according to the difference of the probabilities of the three peaks, and obtaining the function expressions of the red, green and blue three-color Gaussian channels; and finally, passing the gray-level values through the red, green and blue three-color Gaussian channels, merging the output images, and obtaining a processed pseudo-color image. Through adoption of the image gray having approximate Gaussian distribution or a plurality of Gaussian distribution superposition characteristics, the adaptive gray-level image pseudo-color processing method solves the problem that the visual sense effect is not continuous by employing the pseudo-color processing technology in the prior art.

Description

technical field [0001] The invention belongs to the technical field of image processing, in particular to an adaptive grayscale image pseudo-color processing method. Background technique [0002] In the field of medical imaging applications, most images are gray-scale images, such as X-ray, CT, MRI, B-ultrasound images, etc., while the ability of human eyes to distinguish gray levels is poor, and there is little difference for some gray levels, but contains important Grayscale images with detailed information are often unable to be accurately extracted by the human eye. However, the human eye has a high resolution of color. By transforming different gray levels in the image into different colors, the human eye will extract more information, thereby achieving the effect of image enhancement. In order to make use of the human eye's ability to distinguish colors, the pseudo-color processing technology of images was born, that is, the technology of turning grayscale images into...

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Problems solved by technology

[0006] Compared with the prior art, the present invention has significant advantages: (1) Based on the gray-scale probability distribution of the gray-scale image, utilizing the characteristics of the approximate Gaussian distribution or the superposition of multiple Gaussian distributions in the image gray-scale, the gray scale with Gaussian distribution characteristics is adopted. Degree-color mapping transfer function, which solves the problem of discontinuous visual effect of existing pseudo-color processing technology

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