Image noise reduction method and computer readable storage medium
An image noise reduction and image technology, applied in the field of image processing, can solve problems such as poor filtering performance, unfavorable diagnosis, and smear, and achieve the effects of convenient diagnosis, suppressing smear, and suppressing noise
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Embodiment 1
[0063] Please refer to Figure 2-11 , Embodiment 1 of the present invention is: an image noise reduction method, based on time-domain recursive filtering, which can be applied to noise reduction of X-ray fluoroscopy images, such as figure 2 shown, including the following steps:
[0064] S1: Setting the parameters of the image of the first frame, including setting the output image of the first frame and the filter gain of the first frame.
[0065] Specifically, the input image of the first frame (that is, the image of the first frame) can be directly used as the output image of the first frame, that is, x(1,n)=y(1,n); x(t,n ) represents the output image of the t-th frame, y(t,n) represents the input image of the t-th frame, t represents the serial number of the frame, and n represents the pixel index in the image. For the convenience of expression, n can be omitted.
[0066] It is also possible to use other non-recursive methods to perform special processing on the image of ...
Embodiment 2
[0097] This embodiment is a computer-readable storage medium corresponding to the above-mentioned embodiments, on which a computer program is stored, and when the program is executed by a processor, the following steps are implemented:
[0098] Obtain the input image of the current frame and the output image of the previous frame, the input image of the current frame is the image of the current frame;
[0099] calculating the inter-frame grayscale difference between the input image of the current frame and the output image of the previous frame;
[0100] performing truncation processing on the inter-frame grayscale difference according to a preset suppression value and a truncation value;
[0101] Generate the continuity probability curve corresponding to the current frame according to the truncated inter-frame grayscale difference and the preset curve parameters;
[0102] calculating the filter gain of the current frame according to the filter gain of the previous frame and ...
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