An infrared small target detection method based on multi-frame regression deep network
A small target detection and deep network technology, applied in neural learning methods, biological neural network models, image analysis, etc., can solve the problems of inability to accurately locate small targets in real time, reduce false alarm rates, and improve generalization capabilities. , reduce the false alarm rate, and solve the effect of low robustness
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[0059] like figure 1 As shown, a method for detecting small infrared targets based on a multi-frame regression deep network includes the following steps:
[0060] Step 1 includes the following steps:
[0061] Step 1.1: Make a multi-frame infrared small target data set, collect multi-frame infrared small target data and mark the small target, image 3 is an infrared image in the sequence;
[0062] Step 1.2: Perform image preprocessing on the data set produced in Step 1.1, which specifically refers to performing median filtering on all images, that is, the value of any pixel in the small target image is used for each pixel in the neighborhood of the pixel. Values are sorted by median instead.
[0063] Step 2 includes the following steps:
[0064] Step 2.1: For the image preprocessed in step 1.2, first subtract the absolute value of the adjacent two frames of images to obtain two differential images, take the union of the two differential images, and the gray value for the ...
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