Image dynamic range adjustment method and apparatus

Abstract

Embodiments of the invention provide an image dynamic range adjustment method and apparatus. The method comprises: analyzing an original image to obtain a human body tissue foreground image; performing multi-resolution adjustment on the original image to obtain an enhanced image; and determining a nonlinear LUT curve according to an anatomic site type corresponding to the original image and the human body tissue foreground image, and adjusting a dynamic range of the enhanced image by utilizing the nonlinear LUT curve to obtain an output image. According to the embodiments of the invention, different dynamic range adjustment can be performed according to different anatomic site types, so that the gray level distribution range of a region of interest is highlighted, the interference of a background image is reduced, a better image contrast can be provided, richer information can be displayed, and a better display effect can be achieved.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to an image dynamic range adjustment method and device. Background technique [0002] In the technical field of image processing, dynamic range (Dynamic Range) is usually used to represent the relative ratio between the brightest part and the darkest part of an image. The larger the dynamic range of the image, the richer the level of expression and the wider the color space it contains. In the prior art, there are some high dynamic range images, such as digital X-ray images, generally 14 bits can be used to distinguish image brightness, which contains a large amount of information. When a computer represents an image, it usually uses 8 bits to distinguish the brightness of the image, and the dynamic range is small. How to display high dynamic range images on ordinary computers and display richer information in the images has become an important issue. Therefore, it is ne...

AI Technical Summary

Problems solved by technology

It forms a grayscale transformation curve according to the histogram distribution. This method can easily make the processed image histogram smoother, but this method only considers the density distribution of the histogram itself, and the image contrast will be excessively increased so that the image The gray level is discontinuous, so it is difficult to apply to the processing of X-ray images

[0004] There is also a method in the prior art, using a relatively smooth transition nonlinear S-shaped curve to map the image gray level to ensure the continuous distribution of the image gray level, but the simple application of this curve will reduce the contrast of the image to a certain extent and details

[0005] In the process of realizing the present invention, the inventor found that the methods in the prior art simply start from the histogram distribution and the smoothness of the curve, without considering the characteristics of anatomical parts, resulting in some parts being over-processed, poor adaptability, and unable to achieve a good result. The effect of image processing

Images