Xidian University

Hanlin Qin

Huan Li

Jun Zhou

Dong Zhao

Jiangluqi Song

Yue Yu

Bo Yao

Bingjian Wang

Huixin Zhou

Xiuping Jia

Lixin Guo

Kuanhong Cheng

Runda Qian

Rui Lai

Jiajia Zhang

Juan Du

Shangzhen Song

Pei Xiang

Baokai Deng

Yangqun Jin

Shenghui Rong

Kun Qian

Yuanbin Shi

Maosen Huang

An interframe registration and adaptive step size-based non-uniformity correction method for an infrared image, comprising: first calculating a normalized cross-power spectrum of n-th and (n&#x2212;1)-th original infrared images with the non-uniformity, and then calculating a horizontal relative displacement and a vertical relative displacement of the n-th and (n&#x2212;1)-th original infrared images with the non-uniformity; calculating a space variance and a time variance of each pixel of the n-th original infrared image with the non-uniformity, using the obtained space variance and time variance to calculate an adaptive iterative step size of each pixel of the n-th original infrared image with the non-uniformity, and using the iterative step size to update a gain correction coefficient and a bias correction coefficient; finally, performing non-uniformity correction on the pixel in an overlapping area of the n-th and (n&#x2212;1)-th original infrared images with the non-uniformity.

Interframe registration and adaptive step size-based non-uniformity correction method for infrared image

A detection and positioning method for a train water injection port includes: acquiring train water injection port video images, and performing threshold segmentation on the train water injection port video images to obtain binarized train water injection port video images; processing the binarized train water injection port video images and matching the processed binarized train water injection port video images with a train water injection port template image; detecting a position of the water injection port in the train water injection port video image and comparing the position with a pre-set position range where the water injection port is located; and if the position and the pre-set position range have been matched, then transmitting a matching valid signal to a mechanical device control module to control a mechanical device to move or stop and start or stop water injection.

Detection and positioning method for train water injection port

A feature fusion and dense connection-based method for infrared plane object detection includes: constructing an infrared image dataset containing an object to be recognized, calibrating a position and class of the object to be recognized in the infrared image dataset, and obtaining an original known label image; dividing the infrared image dataset into a training set and a validation set; performing image enhancement preprocessing on images in the training set, performing feature extraction and feature fusion, and obtaining classification results and bounding boxes through a regression network; calculating a loss function according to the classification results and the bounding boxes in combination with the original known label image, and updating parameter values of a convolutional neural network; repeating the steps to iteratively update the parameters of the convolutional neural network; and processing images in the validation set through the parameters to obtain a final object detection result map.

Feature fusion and dense connection-based method for infrared plane object detection

A non-uniformity correction method for an infrared image based on guided and high-pass filtering includes: assigning high-frequency component of first image frame of original image sequence to first fixed pattern noise f; successively loading N-th image frame of the original image sequence with non-uniformity as current image frame, determining a difference between the current image frame and (N&#x2212;1)-th image frame to obtain (N&#x2212;1)-th differential image frame, and obtaining a relative change amplitude of each image element of (N&#x2212;1)-th image frame according to the (N&#x2212;1)-th differential image frame; and performing high-pass filtering based on a combination of a high-frequency component of the current image frame obtained through guided filtering and the relative change amplitude to obtain n-th fixed pattern noise f, and performing non-uniformity correction on the current image frame according to fto obtain a correction result of the current image frame, where N&#x2265;2, n&#x2265;2.

Non-uniformity correction method for infrared image based on guided filtering and high-pass filtering

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Xi'an, China

Hanlin Qin