The moving target image has the characteristics of unstable feature points distribution and low SNR of image acquisition

which is not very accurate. Traditional method uses the target recognition algorithm of edge contour feature segmentation

when the image is disturbed by the irregular color noise

the peak signal to noise ratio of the image fusion is low. A moving target image recognition method based on depth pixel image fusion technology is proposed. Gathering under the complex background image of moving targets were wavelet denoising processing

for image noise reduction after purification using texture adaptive quantization density estimation method for image depth super pixel feature segmentation

image principal component edge contour feature information

the input image of moving targets were vector quantization processing

realize image matching and fusion

achieve the purpose of image recognition. The simulation results show that the algorithm is used to deal with the image fusion of moving objects

the root mean square error of the pixel feature matching is low

the peak signal to noise ratio of the output image is improved

and the image recognition accuracy is improved.