[1] Wang S J, Wang J, Liu Y L et al. Estimation of the significant wave height with X-band radars[J]. Transactions of Oceanology and Limnology, 185-190(2009).

[2] Lu Z Z, Yang J H, Huang Y et al. Research on the improvement on the algorithm for retrieving wave height from shadow in marine radar images[J]. Chinese Journal of Scientific Instrument, 38, 212-218(2017).

[3] Duan W Y, Yang K, Huang L M et al. Numerical investigations on wave remote sensing from synthetic X-band radar sea clutter images by using deep convolutional neural networks[J]. Remote Sensing, 12, 1117-1137(2020).

[4] Bozkurt H, Erer I. Information preserving preprocessing for improved radar target classification accuracy[C], 161-165(2017).

[5] Li X W, Huang W M, Peters D K et al. Assessment of synthetic aperture radar image preprocessing methods for iceberg and ship recognition with convolutional neural networks[C], 22-26(2019).

[6] Sun H. Research on the pretreatment of X-band nautical radar sea-surface Image[D], 28-53(2009).

[7] Du Y F. Pretreatment of image based on X-band marine radar[D], 26-30(2015).

[8] Song M Z, Qu H S, Jin G. Weak ship target detection of noisy optical remote sensing image on sea surface[J]. Acta Optica Sinica, 37, 1011004(2017).

[9] Chen R, Jia B Z, Ma L et al. Marine radar oil spill extraction based on texture features and BP neural network[J]. Journal of Marine Science and Engineering, 10, 1904(2022).

[10] Xu Z J, Bai X. Small ship target detection method for remote sensing images based on dual feature enhancement[J]. Acta Optica Sinica, 42, 1828002(2022).

[11] Chen S M, Feng C, Huang Y et al. Small target detection in X-band sea clutter using the visibility graph[J]. IEEE Transactions on Geoscience and Remote Sensing, 60, 5115011(2022).

[12] Zhou Q K, Zhang W, Li D J et al. Ship classification and detection method for optical remote sensing images based on improved YOLOv5s[J]. Laser & Optoelectronics Progress, 59, 1628008(2022).

[13] Wang J L, Lü X Q, Zhang M et al. Remote sensing image ship detection based on improved R-FCN[J]. Laser & Optoelectronics Progress, 56, 162803(2019).

[14] Hojjatoleslami S A, Kittler J. Region growing: a new approach[J]. IEEE Transactions on Image Processing, 7, 1079-1084(1998).

[15] Gong J M, Liu S H, Jin K et al. Image fusion based on improved region growing and guided filtering[J]. Laser & Optoelectronics Progress, 60, 1610009(2023).

[16] Zhang X G, Zhang L Z, Yu D B et al. Automatic spatial distance measurement method for fuel particles based on X-ray micro-CT[J]. Acta Optica Sinica, 43, 0734001(2023).

[17] Wang X L, Du R X, Yao X T et al. Automatic detection and quantitative analysis of insect cardiac function parameters using OCT[J]. Chinese Journal of Lasers, 49, 2007202(2022).

[18] Srinivasa R A, Chenna R P. MRI brain tumor segmentation and prediction using modified region growing and adaptive SVM[J]. Soft Computing, 25, 4135-4148(2021).

[19] Liu Y Z, Li Y P, Dai L Y et al. Motion consistency-based correspondence growing for remote sensing image matching[J]. IEEE Geoscience and Remote Sensing Letters, 19, 8005905(2022).

[20] Zheng Y N. Research and design of X-band marine radar image pre-processor[D], 35-45(2010).