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公开(公告)号：US20220215569A1
公开(公告)日：2022-07-07
申请号：US17603856
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY , PENG CHENG LABORATORY
Inventor： Wei ZHONG , Hong ZHANG , Haojie LI , Zhihui WANG , Risheng LIU , Xin FAN , Zhongxuan LUO , Shengquan LI
Abstract: The present invention belongs to the field of image processing and computer vision, and discloses an acceleration method of depth estimation for multiband stereo cameras. In the process of depth estimation, during binocular stereo matching in each band, through compression of matched images, on one hand, disparity equipotential errors caused by binocular image correction can be offset to make the matching more accurate, and on the other hand, calculation overhead is reduced. In addition, before cost aggregation, cost diagrams are transversely compressed and sparsely matched, thereby reducing the calculation overhead again. Disparity diagrams obtained under different modes are fused to obtain all-weather, more complete and more accurate depth information.
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Patent Agency Ranking
公开(公告)号：US20220028043A1
公开(公告)日：2022-01-27
申请号：US17284394
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Wei ZHONG , Haojie LI , Boqian LIU , Zhihui WANG , Risheng LIU , Zhongxuan LUO , Xin FAN
Abstract: A multispectral camera dynamic stereo calibration algorithm is based on saliency features. The joint self-calibration method comprises the following steps: step 1: conducting de-distortion and binocular correction on an original image according to internal parameters and original external parameters of an infrared camera and a visible light camera. Step 2: Detecting the saliency of the infrared image and the visible light image respectively based on a histogram contrast method. Step 3: Extracting feature points on the infrared image and the visible light image. Step 4: Matching the feature points extracted in the previous step. Step 5: judging a feature point coverage area. Step 6: correcting the calibration result. The present invention solves the change of a positional relationship between an infrared camera and a visible light camera due to factors such as temperature, humidity and vibration.
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13.发明申请公开(公告)号：US20210390339A1
公开(公告)日：2021-12-16
申请号：US17112499
申请日：2020-12-04
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Xinchen YE , Rui XU , Xin FAN
Abstract: The invention discloses a depth estimation and color correction method for monocular underwater images based on deep neural network, which belongs to the field of image processing and computer vision. The framework consists of two parts: style transfer subnetwork and task subnetwork. The style transfer subnetwork is constructed based on generative adversarial network, which is used to transfer the apparent information of underwater images to land images and obtain abundant and effective synthetic labeled data, while the task subnetwork combines the underwater depth estimation and color correction tasks with the stack network structure, carries out collaborative learning to improve their respective accuracies, and reduces the gap between the synthetic underwater image and the real underwater image through the domain adaptation strategy, so as to improve the network's ability to process the real underwater image.
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公开(公告)号：US20220335639A1
公开(公告)日：2022-10-20
申请号：US17437234
申请日：2021-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Qi JIA , Xin FAN , Zhongxuan LUO , Yu LIU , Qian WANG , Risheng LIU , Yi WANG , Xiujuan XU
Abstract: The present invention relates to the technical field of digital image processing, and provides an ellipse detection acceleration method based on generalized Pascal mapping. The method comprises: step 100, extracting accurate edge points from a real image by means an edge detection method of an ellipse detection method, connecting edge points into arcs, and taking a de-noised arc set as input of an ellipse detection acceleration method; step 200, screening out a valid candidate arc combinations probably belonging to the same ellipse from the arc set input in step 100; step 300, calculating five parameters of a candidate ellipse; repeating step 200 to step 300 until all valid candidate arc combinations in the arc set and corresponding candidate ellipses are found; and step 400, clustering and verifying candidate ellipse sets, obtaining a final detected ellipse set.
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公开(公告)号：US20220174256A1
公开(公告)日：2022-06-02
申请号：US17442967
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Weiqiang KONG , Deyun LV , Wei ZHONG , Risheng LIU , Xin FAN , Zhongxuan LUO
IPC: H04N13/271 , G06V10/28 , G06T7/155
Abstract: The present invention discloses a method for infrared small target detection based on a depth map in a complex scene, and belongs to the field of target detection. An infrared image is collected, the image is binarized by using priori knowledge of a to-be-detected target and adopting a pixel value method, the binary image is further limited based on deep priori knowledge, then static and dynamic scoring strategies are formulated to score a candidate connected component in the morphologically processed image, and an infrared small target in a complex scene is detected finally. The method can screen out targets within a specific range, has high reliability; has strong robustness; is simple in program and easy to implement, can be used in sea, land, and air, and has a significant advantage under a complex jungle background.
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16.发明申请公开(公告)号：US20220036589A1
公开(公告)日：2022-02-03
申请号：US17279461
申请日：2020-03-05
Applicant: DALIAN UNIVERSITY OF TECHNOLOGY
Inventor： Wei ZHONG , Boqian LIU , Haojie LI , Zhihui WANG , Risheng LIU , Xin FAN , Zhongxuan LUO
IPC: G06T7/80 , H04N13/239 , H04N13/156 , H04N13/25 , G06T7/13
Abstract: The present invention discloses a multispectral camera external parameter self-calibration algorithm based on edge features, and belongs to the field of image processing and computer vision. Because a visible light camera and an infrared camera belong to different modes, fewer satisfactory point pairs are obtained by directly extracting and matching feature points. In order to solve the problem, the method starts from the edge features, and finds an optimal corresponding position of an infrared image on a visible light image through edge extraction and matching. In this way, a search range is reduced and the number of the satisfactory matched point pairs is increased, thereby more effectively conducting joint self-calibration on the infrared camera and the visible light camera. The operation is simple and results are accurate.
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