Real time three-dimensional image smoothing process method based on pattern processor

Abstract

The invention provides a real-time three-dimensional image smooth processing method based on graphics processing units. The method orderly comprises the following steps that: (1) the data of a three-dimensional image to be processed is transmitted to a graphics processing units; (2) coordinates of related points around a pixel point to be processed are figured out; (3) the related points are sampled, so as to obtain the data values of the related points; (4) the average value of the data values of the related data points is calculated; (5) the squares of the difference of the data values of the related data points and the average value are respectively calculated, and the numerical values calculated are saved in an array; (6) the numerical values in the array are compared, and a minimum value is figured out; (7) the prior data value of the pixel point to be processed is replaced by the data value of the related data point corresponding to the minimum value; and the steps (2) to (7) are carried out in the graphics processing units. The method can eliminate the speckle noise of the three-dimensional image, beautify the image and well preserve the prior boundary information of the image without affecting the real-time performance of three-dimensional image reconstruction.

Description

technical field [0001] The invention relates to image data processing, in particular to a real-time three-dimensional image smoothing processing method based on a graphics processor. Background technique [0002] The purpose of smoothing the image is to remove the speckle noise in the image and beautify the image. Existing image smoothing methods are all based on a central processing unit (CPU). For a two-dimensional image, real-time smoothing can be well realized because the amount of image data is not very large. [0003] However, when the amount of image data is large, for example, for three-dimensional image data (that is, volumetric image data), it is difficult to meet the requirement of real-time smoothing processing. The image formed by the real-time 3D image reconstruction method based on a graphics processing unit (GPU) will inevitably have some speckle noise. To reduce or remove these speckle noise, there may be millions or even tens of millions of speckle noises ...

AI Technical Summary

Problems solved by technology

[0003] However, when the amount of image data is large, such as three-dimensional image data (ie, volume image data), the real-time performance of smoothing processing is difficult to meet the requirements

The image formed by the real-time 3D image reconstruction method based on the graphics processing unit (GPU) will inevitably have some speckle noise. The pixels need to be processed, and the amount of calculation is quite large. It will take a long time to use the CPU to process, which is a very heavy burden on the CPU and will seriously affect the real-time performance of 3D image reconstruction.

Images