Aerial infrared small target detection algorithm combined structure tensor and local contrast

• Autorzy: Wang Zhonghua , He Bangsheng , He Wenjie

Identyfikatory

DOI

10.37190/oa240307

• Języki publikacji: EN

Abstrakty

EN

To solve the problem of false alarm rate in detecting infrared small targets under complex cloud backgrounds, a novel algorithm combining structure tensor and local contrast is proposed. The structure tensor can better describe the gradient distributions in the local image area, and its eigenvalues can also depict the characteristics of the area. Combining the weighted local contrast with eigenvalues, the small targets can be enhanced and the background can be suppressed. In addition, to highlight the target, the regional complexity is further used for weighting local contrast. The presented algorithm steps are as follows: firstly, Gaussian filtering is performed on the original image; secondly, the larger eigenvalue of the structure tensor matrix is used to calculate the local contrast through the difference operation; thirdly, the regional complexity is calculated by the gray difference between the central and surrounding regions for weighting the local contrast to generate a saliency map; finally, an adaptive threshold segmentation is performed on the saliency map to extract the real target. The comparative experiments show that the proposed algorithm can achieve the highest detection rate, lowest false alarm rate, and shortest running time.

Słowa kluczowe

EN

adaptive threshold segmentation; local contrast; regional complexity; small target; structure tensor

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2024
• Tom: Vol. 54, nr 3
• Strony: 365--381
• Opis fizyczny: Bibliogr. 37 poz., rys., tab.

Twórcy

autor

Wang Zhonghua

• School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China

autor

He Bangsheng

• School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China

autor

He Wenjie

• School of Information Engineering, Nanchang Hangkong University, Nanchang 330063, China

Bibliografia

• [1] DU J., LU H., ZHANG L., HU M., CHEN S., DENG Y., A spatial-temporal feature-based detection framework for infrared dim small target, IEEE Transactions on Geoscience and Remote Sensing 60, 2022: 3000412. https://doi.org/10.1109/TGRS.2021.3117131
• [2] WANG G., TAO B., KONG X., PENG Z., Infrared small target detection using nonoverlapping patch spatial–temporal tensor factorization with capped nuclear norm regularization, IEEE Transactions on Geoscience and Remote Sensing 60, 2022: 5001417. https://doi.org/10.1109/TGRS.2021.3126608
• [3] WANG H., LIU C., MA C., MA S., A novel and high-speed local contrast method for infrared small-target detection, IEEE Geoscience and Remote Sensing Letters 17(10), 2020: 1812-1816. https://doi.org/10.1109/LGRS.2019.2951918
• [4] DAI Y., WU Y., ZHOU F., BARNARD K., Attentional local contrast networks for infrared small target detection, IEEE Transactions on Geoscience and Remote Sensing 59(11), 2021: 9813-9824. https://doi.org/10.1109/TGRS.2020.3044958
• [5] QIN Y., BRUZZONE L., GAO C., LI B., Infrared small target detection based on facet kernel and random walker, IEEE Transactions on Geoscience and Remote Sensing 57(9), 2019: 7104-7118. https://doi.org/10.1109/TGRS.2019.2911513
• [6] QIU Z., MA Y., FAN F., HUANG J., WU M., Adaptive scale patch-based contrast measure for dim and small infrared target detection, IEEE Geoscience and Remote Sensing Letters 19, 2022: 7000305. https://doi.org/10.1109/LGRS.2020.3036842
• [7] WANG K., DU S., LIU C., CAO Z., Interior attention-aware network for infrared small target detection, IEEE Transactions on Geoscience and Remote Sensing 60, 2022: 5002013. https://doi.org/10.1109/TGRS.2022.3163410
• [8] ZHANG K., YANG K., LI S., CHEN H.-B., A difference-based local contrast method for infrared small target detection under complex background, IEEE Access 7, 2019: 105503-105513. https://doi.org/10.1109/ACCESS.2019.2932729
• [9] HAN J., LIU S., QIN G., ZHAO Q., ZHANG H., LI N., A local contrast method combined with adaptive background estimation for infrared small target detection, IEEE Geoscience and Remote Sensing Letters 16(9), 2019: 1442-1446. https://doi.org/10.1109/LGRS.2019.2898893
• [10] ZHANG P., ZHANG L., WANG X., SHEN F., PU T., FEI C., Edge and corner awareness-based spatial–temporal tensor model for infrared small-target detection, IEEE Transactions on Geoscience and Remote Sensing 59(12), 2021: 10708-10724. https://doi.org/10.1109/TGRS.2020.3037938
• [11] SADJADI F.A., Infrared target detection with probability density functions of wavelet transform subbands, Applied Optics 43(2), 2004: 315-323. https://doi.org/10.1364/AO.43.000315
• [12] BAI X., ZHOU F., Analysis of new top-hat transformation and the application for infrared dim small target detection, Pattern Recognition 43(6), 2010: 2145-2156. https://doi.org/10.1016/j.patcog.2009.12.023
• [13] DESHPANDE S.D., ER M.H., VENKATESWARLU R., CHAN P., Max-mean and max-median filters for detection of small targets, Proceedings of the SPIE, Vol. 3809, Signal and Data Processing of Small Targets 1999: 74-83. https://doi.org/10.1117/12.364049
• [14] PANG D., SHAN T., LI W., MA P., TAO R., MA Y., Facet derivative-based multidirectional edge awareness and spatial–temporal tensor model for infrared small target detection, IEEE Transactions on Geoscience and Remote Sensing 60, 2022: 5001015. https://doi.org/10.1109/TGRS.2021.3098969
• [15] LIU T., YANG J., LI B., XIAO C., SUN Y., WANG Y., Nonconvex tensor low-rank approximation for infrared small target detection, IEEE Transactions on Geoscience and Remote Sensing 60, 2022: 5614718. https://doi.org/10.1109/TGRS.2021.3130310
• [16] XIONG B., HUANG X., WANG M., Local gradient field feature contrast measure for infrared small target detection, IEEE Geoscience and Remote Sensing Letters 18(3), 2021: 553-557. https://doi.org/ 10.1109/LGRS.2020.2976208
• [17] HAN J., LIANG K., ZHOU B., ZHU X., ZHAO J., ZHAO L., Infrared small target detection utilizing the multiscale relative local contrast measure, IEEE Geoscience and Remote Sensing Letters 15(4), 2018: 612-616. https://doi.org/10.1109/LGRS.2018.2790909
• [18] SUN Y., YANG J., AN W., Infrared dim and small target detection via multiple subspace learning and spatial-temporal patch-tensor model, IEEE Transactions on Geoscience and Remote Sensing 59(5), 2021: 3737-3752. https://doi.org/10.1109/TGRS.2020.3022069
• [19] HAN J., MORADI S., FARAMARZI I., LIU C., ZHANG H., ZHAO Q., A local contrast method for infrared small-target detection utilizing a tri-layer window, IEEE Geoscience and Remote Sensing Letters 17(10), 2020: 1822-1826. https://doi.org/10.1109/LGRS.2019.2954578
• [20] YAN Z., XIN Y., ZHANG Y., Local contrast measure with iterative error for infrared small target detection, IET Image Processing 14(15), 2020: 3725-3732. https://doi.org/10.1049/iet-ipr.2020.1157
• [21] CHEN C.L.P., LI H., WEI Y., XIA T., TANG Y.Y., A local contrast method for small infrared target detection, IEEE Transactions on Geoscience and Remote Sensing 52(1), 2014: 574-581. https://doi.org/10.1109/TGRS.2013.2242477
• [22] ZHANG X., DING Q., LUO H., HUI B., CHANG Z., ZHANG J., Infrared dim target detection algorithm based on improved LCM, Infrared and Laser Engineering 46(7), 2017: 726002. https://doi.org/10.3788/irla201746.0726002
• [23] DU P., HAMDULLA A., Infrared small target detection using homogeneity-weighted local contrast measure, IEEE Geoscience and Remote Sensing Letters 17(3), 2020: 514-518. https://doi.org/ 10.1109/LGRS.2019.2922347
• [24] HAN J., MORADI S., FARAMARZI I., ZHANG H., ZHAO Q., ZHANG X., Infrared small target detection based on the weighted strengthened local contrast measure, IEEE Geoscience and Remote Sensing Letters 18(9), 2021: 1670-1674. https://doi.org/10.1109/LGRS.2020.3004978
• [25] CHEN Y., HAN J., ZHANG H., SANG X., Infrared small dim target detection using local contrast measure weighted by reversed local diversity, Infrared and Laser Engineering 50(8), 2021: 20200418. https://doi.org/10.3788/IRLA20200418
• [26] LU R., YANG X., LI W., FAN J., LI D., JING X., Robust infrared small target detection via multidirectional derivative-based weighted contrast measure, IEEE Geoscience and Remote Sensing Letters 19, 2022: 7000105. https://doi.org/10.1109/LGRS.2020.3026546
• [27] DENG H., SUN X., LIU M., YE C., ZHOU X., Small infrared target detection based on weighted local difference measure, IEEE Transactions on Geoscience and Remote Sensing 54(7), 2016: 4204-4214. https://doi.org/10.1109/TGRS.2016.2538295
• [28] DONG L., WANG B., ZHAO M., XU W., Robust infrared maritime target detection based on visual attention and spatiotemporal filtering, IEEE Transactions on Geoscience and Remote Sensing 55(5), 2017: 3037-3050. https://doi.org/10.1109/TGRS.2017.2660879
• [29] SHI Y., WEI Y., YAO H., PAN D., XIAO G., High-boost-based multiscale local contrast measure for infrared small target detection, IEEE Geoscience and Remote Sensing Letters 15(1), 2018: 33-37. https://doi.org/10.1109/LGRS.2017.2772030
• [30] XIA C., LI X., ZHAO L., SHU R., Infrared small target detection based on multiscale local contrast measure using local energy factor, IEEE Geoscience and Remote Sensing Letters 17(1), 2020: 157-161. https://doi.org/10.1109/LGRS.2019.2914432
• [31] GUAN X., PENG Z., HUANG S., CHEN Y., Gaussian scale-space enhanced local contrast measure for small infrared target detection, IEEE Geoscience and Remote Sensing Letters 17(2), 2020: 327-331. https://doi.org/10.1109/LGRS.2019.2917825
• [32] MORADI S., MOALLEM P., SABAHI M.F., Scale-space point spread function based framework to boost infrared target detection algorithms, Infrared Physics & Technology 77, 2016: 27-34. https://doi.org/10.1016/j.infrared.2016.05.007
• [33] QIN Y., LI B., Effective infrared small target detection utilizing a novel local contrast method, IEEE Geoscience and Remote Sensing Letters 13(12), 2016: 1890-1894. https://doi.org/10.1109/LGRS.2016.2616416
• [34] HAN J., JIANG Y., ZHANG X., LIANG K., LI Z., DONG X., LI N., Infrared small target detection using tri-layer window local contrast, Infrared and Laser Engineering, 50(2), 2021: 20200146. https://doi.org/10.3788/IRLA20200146
• [35] DUAN S., WANG Z., YE Z., An infrared small object detection algorithm based on spatial weighted local contrast, Laser and Infrared 50(10), 2020: 1200-1206.
• [36] ZHANG C., HE Y., TANG Q., CHEN Z., MU T., Infrared small target detection via interpatch correlation enhancement and joint local visual saliency prior, IEEE Transactions on Geoscience and Remote Sensing 60, 2022: 5001314. https://doi.org/10.1109/TGRS.2021.3128189
• [37] BAI X., BI Y., Derivative entropy-based contrast measure for infrared small-target detection, IEEE Transactions on Geoscience and Remote Sensing 56(4), 2018: 2452-2466. https://doi.org/10.1109/TGRS.2017.2781143