[1] RenX, MalikJ. Learning a classification model for segmentation[C]∥Proceedings of the Ninth IEEE International Conference on Computer Vision, 2003: 10- 17.

[2] 宋熙煜, 周利莉, 李中国, 等. 图像分割中的超像素方法研究综述[J]. 中国图象图形学报, 2015, 20(5): 599-608.

    Song X Y, Zhou L L, Li Z G, et al. Review on superpixel methods in image segmentation[J]. Journal of Image and Graphics, 2015, 20(5): 599-608.

[3] 王春瑶, 陈俊周, 李炜. 超像素分割算法研究综述[J]. 计算机应用研究, 2014, 31(1): 6-12.

    Wang C Y, Chen J Z, Li W. Review on superpixel segmentation algorithms[J]. Application Research of Computers, 2014, 31(1): 6-12.

[4] Gong YJ, Zhou YC, Zhang XL. A superpixel segmentation algorithm based on differential evolution[C]∥2016 IEEE International Conference on Multimedia and Expo (ICME), 2016: 1- 6.

[5] Gong Y J, Zhou Y C. Differential evolutionary superpixel segmentation[J]. IEEE Transactions on Image Processing, 2018, 27(3): 1390-1404.

[6] Nakamura K, Hong B W. Fast-convergence superpixel algorithm via an approximate optimization[J]. Journal of Electronic Imaging, 2016, 25(5): 053035.

[7] Peng J T, Shen J B, Yao A, et al. Superpixel optimization using higher order energy[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2016, 26(5): 917-927.

[8] Chen J S, Li Z Q, Huang B. Linear spectral clustering superpixel[J]. IEEE Transactions on Image Processing, 2017, 26(7): 3317-3330.

[9] Achanta R, Shaji A, Smith K, et al. SLIC superpixels compared to state-of-the-art superpixel methods[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(11): 2274-2282.

[10] Shen J B, Hao X P, Liang Z Y, et al. Real-time superpixel segmentation by DBSCAN clustering algorithm[J]. IEEE Transactions on Image Processing, 2016, 25(12): 5933-5942.

[11] Zhao J, Bo R, Hou Q, et al. FLIC: fast linear iterative clustering with active search[J]. Computational Visual Media, 2018, 4(4): 333-348.

[12] Xiao X L, Zhou Y C, Gong Y J. Content-adaptive superpixel segmentation[J]. IEEE Transactions on Image Processing, 2018, 27(6): 2883-2896.

[13] Ban Z H, Liu J G, Cao L. Superpixel segmentation using gaussian mixture model[J]. IEEE Transactions on Image Processing, 2018, 27(8): 4105-4117.

[14] Hu Y L, Li Y S, Song R, et al. Minimum barrier superpixel segmentation[J]. Image and Vision Computing, 2018, 70: 1-10.

[15] Wang P, Zeng G, Gan R, et al. Structure-sensitive superpixels via geodesic distance[J]. International Journal of Computer Vision, 2013, 103(1): 1-21.

[16] Giraud R, Ta V T, Papadakis N. Robust superpixels using color and contour features along linear path[J]. Computer Vision and Image Understanding, 2018, 170: 1-13.

[17] Fang Z Q, Yu X S, Wu C D, et al. Superpixel segmentation using weighted coplanar feature clustering on RGBD images[J]. Applied Sciences, 2018, 8(6): 902.

[18] Zhang Y X, Li X M, Gao X F, et al. A simple algorithm of superpixel segmentation with boundary constraint[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2017, 27(7): 1502-1514.

[19] Huang C R, Wang W C, Wang W A, et al. USEAQ: ultra-fast superpixel extraction via adaptive sampling from quantized regions[J]. IEEE Transactions on Image Processing, 2018, 27(10): 4916-4931.

[20] AchantaR, SüsstrunkS. Superpixels and polygons using simple non-iterative clustering[C]∥2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017: 4895- 4904.

[21] BaiY, Chen XJ. Efficient structure-preserving superpixel segmentation based on minimum spanning tree[C]∥2016 IEEE International Conference on Multimedia and Expo (ICME), 2016: 1- 6.

[22] Chaibou M S, Conze P H, Kalti K, et al. Adaptive strategy for superpixel-based region-growing image segmentation[J]. Journal of Electronic Imaging, 2017, 26(6): 061605.

[23] Chai D F, Huang Y T, Bao Y J. IRSL: iterative refining superpixel lattice[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(3): 344-348.

[24] Moore AP, Prince S J D, Warrell J, et al. Superpixel lattices[C]∥2008 IEEE Conference on Computer Vision and Pattern Recognition, 2008: 1- 8.

[25] ZhaoQ, WanL, Zhang JW. Spherical superpixel segmentation[C]∥2016 IEEE International Conference on Multimedia and Expo (ICME), 2016: 1- 6.

[26] Zhao Q, Dai F, Ma Y K, et al. Spherical superpixel segmentation[J]. IEEE Transactions on Multimedia, 2018, 20(6): 1406-1417.

[27] Amami A, Azouz Z B. Alouane M T H. AdaSLIC: adaptive supervoxel generation for volumetric medical images[J]. Multimedia Tools and Applications, 2019, 78(3): 3723-3745.

[28] Zhang Y X, Ma L, Zhou Y F, et al. Automatic superpixel generation algorithm based on a quadric error metric in 3D space[J]. Signal, Image and Video Processing, 2017, 11(3): 471-478.

[29] Cai Y Q, Guo X H. Anisotropic superpixel generation based on mahalanobis distance[J]. Computer Graphics Forum, 2016, 35(7): 199-207.

[30] 苏腾飞, 张圣微, 李洪玉. 种子区域生长的高分遥感影像超像素分割[J]. 测绘科学, 2018, 43(8): 122-129.

    Su T F, Zhang S W, Li H Y. High resolution remote sensing image super-pixel segmentation based on seeded region growing[J]. Science of Surveying and Mapping, 2018, 43(8): 122-129.

[31] Wang W, Xiang D L, Ban Y F, et al. Superpixel segmentation of polarimetric SAR images based on integrated distance measure and entropy rate method[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2017, 10(9): 4045-4058.

[32] Felzenszwalb P F, Huttenlocher D P. Efficient graph-based image segmentation[J]. International Journal of Computer Vision, 2004, 59(2): 167-181.

[33] Levinshtein A, Stere A, Kutulakos K N, et al. TurboPixels: fast superpixels using geometric flows[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2009, 31(12): 2290-2297.

[34] VedaldiA, SoattoS. Quick shift and kernel methods for mode seeking[M] ∥Vedaldi A, Soatto S. eds. Heidelberg: Springer, 2008 : 705- 718.

[35] StutzD. Superpixel segmentation: an evaluation[M] ∥Stutz D. Cham: Springer International Publishing, 2015: 555- 562.

[36] MathieuB, CrouzilA, Puel JB. Over segmentation methods: a new evaluation[M] ∥Mathieu B, Crouzil A, Puel J B. Cham: Springer International Publishing, 2017: 185- 193.

[37] LiuM, TuzelO, RamalingamS, et al. Entropy rate superpixel segmentation[C] ∥Proceedings of Computer Vision and Pattern Recognition, 2011: 2097- 2104.

[38] Zhang YH, HartleyR, MashfordJ, et al. Superpixels via pseudo-Boolean optimization[C]∥2011 International Conference on Computer Vision, 2011: 1387- 1394.

[39] ConradC, MertzM, MesterR. Contour-relaxed superpixels[M] ∥Conrad C, Mertz M, Mester R. Heidelberg: Springer, 2013: 280- 293.

[40] TangD, Fu HZ, Cao XC. Topology preserved regular superpixel[C]∥2012 IEEE International Conference on Multimedia and Expo, 2012: 765- 768.

[41] Stutz D, Hermans A, Leibe B. Superpixels: an evaluation of the state-of-the-art[J]. Computer Vision and Image Understanding, 2018, 166: 1-27.

[42] GouldS, FultonR, KollerD. Decomposing a scene into geometric and semantically consistent regions[C]∥2009 IEEE 12th International Conference on Computer Vision, 2009: 1- 8.

[43] Song SR, Lichtenberg SP, Xiao JX. SUN RGB-D: a RGB-D scene understanding benchmark suite[C]∥2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015: 567- 576.

[44] YamaguchiK, Kiapour MH, Ortiz LE, et al. Parsing clothing in fashion photographs[C]∥IEEE Conference on Computer Vision and Pattern Recognition, 2012: 3570- 3577.

[45] GiraudR, Ta VT, PapadakisN. Robust shape regularity criteria for superpixel evaluation[C]∥IEEE International Conference on Image Processing, 2017: 3455- 3459.

[46] Giraud R, Ta V T, Papadakis N. Evaluation framework of superpixel methods with a global regularity measure[J]. Journal of Electronic Imaging, 2017, 26(6): 061603.

[47] Brekhna B, Mahmood A, Zhou Y F. Robustness analysis of superpixel algorithms to image blur, additive Gaussian noise, and impulse noise[J]. Journal of Electronic Imaging, 2017, 26(6): 061604.

[48] 王成敏, 杨学志, 周芳. SAR图像超像素生成算法抗噪性能研究[J]. 合肥工业大学学报(自然科学版), 2016, 39(12): 1626-1632.

    Wang C M, Yang X Z, Zhou F. Research on anti-noise performance of superpixel segmentation algorithms of SAR image[J]. Journal of Hefei University of Technology (Natural Science), 2016, 39(12): 1626-1632.

[49] Zhang L G, Verma B, Stockwell D. Spatial contextual superpixel model for natural roadside vegetation classification[J]. Pattern Recognition, 2016, 60: 444-457.

[50] Arisoy S, Kayabol K. Mixture-based superpixel segmentation and classification of SAR images[J]. IEEE Geoscience and Remote Sensing Letters, 2016, 13(11): 1721-1725.

[51] FanF, MaY, LiC, et al. Hyperspectral image denoising with superpixel segmentation and low-rank representation[J]. InformationSciences, 2017, 397/398: 48- 68.

[52] Jin X D, Gu Y F. Superpixel-based intrinsic image decomposition of hyperspectral images[J]. IEEE Transactions on Geoscience and Remote Sensing, 2017, 55(8): 4285-4295.

[53] Pappas O, Achim A, Bull D. Superpixel-level CFAR detectors for ship detection in SAR imagery[J]. IEEE Geoscience and Remote Sensing Letters, 2018, 15(9): 1397-1401.

[54] Li T, Liu Z, Xie R, et al. An improved superpixel-level CFAR detection method for ship targets in high-resolution SAR images[J]. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2018, 11(1): 184-194.

[55] Giraud R, Ta V T, Bugeau A, et al. SuperPatchMatch: an algorithm for robust correspondences using superpixel patches[J]. IEEE Transactions on Image Processing, 2017, 26(8): 4068-4078.

[56] Jiang J J, Ma J Y, Chen C, et al. SuperPCA: a superpixel wise PCA approach for unsupervised feature extraction of hyperspectral imagery[J]. IEEE Transactions on Geoscience and Remote Sensing, 2018, 56(8): 4581-4593.

[57] Sun W, Liao Q M, Xue J H, et al. SPSIM: a superpixel-based similarity index for full-reference image quality assessment[J]. IEEE Transactions on Image Processing, 2018, 27(9): 4232-4244.

[58] Boemer F, Ratner E, Lendasse A. Parameter-free image segmentation with SLIC[J]. Neurocomputing, 2018, 277: 228-236.

[59] Gangapure V N, Nanda S, Chowdhury A S. Superpixel-based causal multisensor video fusion[J]. IEEE Transactions on Circuits and Systems for Video Technology, 2018, 28(6): 1263-1272.

[60] 闫琦, 李慧, 荆林海, 等. 一种超像素区域相似性度量的遥感信息提取算法[J]. 激光与光电子学进展, 2017, 54(8): 081004.

    Yan Q, Li H, Jing L H, et al. An extraction algorithm of remote sensing information based on similarity measurement for superpixel regions[J]. Laser & Optoelectronics Progress, 2017, 54(8): 081004.

[61] 郭呈呈, 于凤芹, 陈莹. 基于卷积神经网络特征和改进超像素匹配的图像语义分割[J]. 激光与光电子学进展, 2018, 55(8): 081005.

    Guo C C, Yu F Q, Chen Y. Image semantic segmentation based on convolutional neural network feature and improved superpixel matching[J]. Laser & Optoelectronics Progress, 2018, 55(8): 081005.