{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,18]],"date-time":"2026-04-18T09:30:35Z","timestamp":1776504635740,"version":"3.51.2"},"reference-count":60,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2019,5,18]],"date-time":"2019-05-18T00:00:00Z","timestamp":1558137600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Synthetic aperture radar (SAR) images map Earth\u2019s surface at high resolution, regardless of the weather conditions or sunshine phenomena. Therefore, SAR images have applications in various fields. Speckle noise, which has the characteristic of multiplicative noise, degrades the image quality of SAR images, which causes information loss. This study proposes a speckle noise reduction algorithm while using the speckle reducing anisotropic diffusion (SRAD) filter, discrete wavelet transform (DWT), soft threshold, improved guided filter (IGF), and guided filter (GF), with the aim of removing speckle noise. First, the SRAD filter is applied to the SAR images, and a logarithmic transform is used to convert multiplicative noise in the resulting SRAD image into additive noise. A two-level DWT is used to divide the resulting SRAD image into one low-frequency and six high-frequency sub-band images. To remove the additive noise and preserve edge information, horizontal and vertical sub-band images employ the soft threshold; the diagonal sub-band images employ the IGF; while, the low- frequency sub-band image removes additive noise using the GF. The experiments used both standard and real SAR images. The experimental results reveal that the proposed method, in comparison to state-of-the art methods, obtains excellent speckle noise removal, while preserving the edges and maintaining low computational complexity.<\/jats:p>","DOI":"10.3390\/rs11101184","type":"journal-article","created":{"date-parts":[[2019,5,20]],"date-time":"2019-05-20T11:05:07Z","timestamp":1558350307000},"page":"1184","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":110,"title":["Speckle Noise Reduction Technique for SAR Images Using Statistical Characteristics of Speckle Noise and Discrete Wavelet Transform"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4995-9039","authenticated-orcid":false,"given":"Hyunho","family":"Choi","sequence":"first","affiliation":[{"name":"Department of Electronics and Computer Engineering, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3759-3116","authenticated-orcid":false,"given":"Jechang","family":"Jeong","sequence":"additional","affiliation":[{"name":"Department of Electronics and Computer Engineering, Hanyang University, 222, Wangsimni-ro, Seongdong-gu, Seoul 04763, Korea"}]}],"member":"1968","published-online":{"date-parts":[[2019,5,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"6257","DOI":"10.1109\/TGRS.2013.2295824","article-title":"Subspace-Based Technique for Speckle Noise Reduction in SAR Images","volume":"52","author":"Yahya","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"730","DOI":"10.1109\/TGRS.2017.2754420","article-title":"A Hybrid Method of SAR Speckle Reduction Based on Geometric-Structural Block and Adaptive Neighborhood","volume":"56","author":"Liu","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Guo, F., Zhang, G., Zhang, Q., Zhao, R., Deng, M., and Xu, K. (2018). Speckle Suppression by Weighted Euclidean Distance Anisotropic Diffusion. Remote Sens., 10.","DOI":"10.3390\/rs10050722"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1205","DOI":"10.1109\/TGRS.2018.2865197","article-title":"Hyperspectral image denoising employing a spatial-spectral deep residual convolutional neural network","volume":"57","author":"Yuan","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4274","DOI":"10.1109\/TGRS.2018.2810208","article-title":"Missing data reconstruction in remote sensing image with a unified spatial-temporal-spectral deep convolutional neural network","volume":"56","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1779","DOI":"10.1109\/TGRS.2018.2869101","article-title":"Remote sensing image scene classification using rearranged local features","volume":"57","author":"Yuan","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1573","DOI":"10.1109\/TGRS.2018.2867444","article-title":"Density peak-based noisy label detection for hyperspectral image classification","volume":"57","author":"Tu","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2633","DOI":"10.1109\/TGRS.2017.2769710","article-title":"An automatic data-driven method for SAR image segmentation in sea surface analysis","volume":"56","author":"Gemme","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_9","first-page":"5997","article-title":"Adaptive hierarchical multinomial latent model with hybrid kernel function for SAR image semantic segmentation","volume":"56","author":"Duan","year":"2018","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.neucom.2016.09.028","article-title":"SAR despeckling via classification-based nonlocal and local sparse representation","volume":"219","author":"Liu","year":"2017","journal-title":"Neurocomputing"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"721","DOI":"10.1109\/TGRS.2002.1000333","article-title":"Statistical properties of logarithmically transformed speckle","volume":"40","author":"Xie","year":"2002","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"844","DOI":"10.1109\/TPAMI.2002.1008390","article-title":"A fundamental relationship between bilateral filtering, adaptive smoothing and the nonlinear diffusion equation","volume":"24","author":"Barash","year":"2002","journal-title":"IEEE Trans. Pattern Anal. Machine Intell."},{"key":"ref_13","unstructured":"Tomasi, C., and Manduchi, R. (1998, January 4\u20137). Bilateral Filtering for Gray and Color Images. Proceedings of the Sixth International Conference on Computer Vision, Bombay, India."},{"key":"ref_14","unstructured":"Buades, A., Coll, B., and Morel, J.-M. (2005, January 20\u201325). A non-local algorithm for image denoising. Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, San Diego, CA, USA."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Buades, A., Coll, B., and Morel, J.M. (2005). A review of image denoising algorithms, with a new one. SIAM Multiscale Model. Simul., 490\u2013530.","DOI":"10.1137\/040616024"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Torres, L., Sant\u2019Anna, S.J.S., Freitas, C.D.C., and Frery, C. (2014). Speckle reduction in polarimetric SAR imagery with stochastic distances and nonlocal means. Pattern Recognit., 141\u2013157.","DOI":"10.1016\/j.patcog.2013.04.001"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2843","DOI":"10.1364\/AO.56.002843","article-title":"Combination of oriented partial differential equation and shearlet transform for denoising in electronic speckle pattern interferometry fringe patters","volume":"56","author":"Xu","year":"2017","journal-title":"Appl. Opt."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"629","DOI":"10.1109\/34.56205","article-title":"Scale-Space and Edge Detection Using Anisotropic Diffusion","volume":"12","author":"Perona","year":"1990","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"099501","DOI":"10.7498\/aps.62.099501","article-title":"Speckle reduction by image entropy anisotropic diffusion","volume":"62","author":"Li","year":"2013","journal-title":"Acta Phys. Sin."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2661","DOI":"10.1109\/TIP.2009.2029593","article-title":"Iterative weighted maximum likelihood denoising with probabilistic patch-based weights","volume":"18","author":"Deledalle","year":"2009","journal-title":"IEEE Trans. Image Process."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.ultras.2015.10.005","article-title":"Speckle filtering of medical ultrasonic images using wavelet and guided filter","volume":"65","author":"Zhang","year":"2016","journal-title":"Ultrasonics"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"6181","DOI":"10.1109\/TGRS.2013.2295431","article-title":"Two-step multitemporal nonlocal means for synthetic aperture radar images","volume":"52","author":"Su","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"5467","DOI":"10.1109\/TGRS.2017.2707806","article-title":"Multitemporal SAR image despeckling based on block-matching and collaborative filtering","volume":"55","author":"Chierchia","year":"2017","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1109\/TGRS.2011.2161586","article-title":"A nonlocal SAR image denoising algorithm based on LLMMSE wavelet shrinkage","volume":"50","author":"Parrilli","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.ins.2018.09.058","article-title":"Wavelet transform based on Meyer algorithm for image edge and blocking artifact reduction","volume":"474","author":"Wu","year":"2019","journal-title":"Inf. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.inffus.2012.09.005","article-title":"Fusion of multimodal medical images using Daubechies complex wavelet transform\u2014A multiresolution approach","volume":"19","author":"Singh","year":"2014","journal-title":"Inform. Fusion"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1006\/gmip.1995.1022","article-title":"Multisensor image fusion using the wavelet transform","volume":"57","author":"Li","year":"1995","journal-title":"Graph. Models Image Process."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1855","DOI":"10.1016\/j.patcog.2004.03.010","article-title":"A wavelet-based image fusion tutorial","volume":"37","author":"Pajares","year":"2004","journal-title":"Pattern Recognit."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.inffus.2014.06.001","article-title":"Face recognition based on pixel-level and feature-level fusion of the top-level\u2019s wavelet sub-bands","volume":"22","author":"Huang","year":"2015","journal-title":"Inf. Fusion"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.sigpro.2013.09.007","article-title":"Efficient modified directional lifting-based discrete wavelet transform for moving object detection","volume":"96","author":"Hsia","year":"2014","journal-title":"Signal Process."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"3918","DOI":"10.1109\/TIP.2018.2828329","article-title":"A Fusion Framework for Camouflaged Moving Foreground Detection in the Wavelet Domain","volume":"27","author":"Liu","year":"2018","journal-title":"IEEE Trans. Image Process."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"613","DOI":"10.1109\/18.382009","article-title":"De-noising by soft-thresholding","volume":"25","author":"Donoho","year":"1995","journal-title":"IEEE Trans. Inf. Theory"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1200","DOI":"10.1080\/01621459.1995.10476626","article-title":"Adapting to unknown smoothness via wavelet shrinkage","volume":"90","author":"Donoho","year":"1995","journal-title":"J. Am. Stat. Assoc."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1532","DOI":"10.1109\/83.862633","article-title":"Adaptive wavelet thresholding for image denoising and compression","volume":"9","author":"Chang","year":"2000","journal-title":"IEEE Trans. Image Process."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Yang, Y., Ding, Z., Liu, J., Gao, Q., Yuan, X., and Lu, X. (2017, January 23\u201328). An adaptive SAR image speckle noise algorithm based on wavelet transform and diffusion equations for marine scenes. Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium, Fort Worth, TX, USA.","DOI":"10.1109\/IGARSS.2017.8127650"},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Amini, M., Ahmad, M.O., and Swamy, M.N.S. (2016, January 15\u201318). SAR image despeckling using vector-based hidden markov model in wavelet domain. Proceedings of the 2016 IEEE Canadian Conference on Electrical and Computer Engineering, Vancouver, BC, Canada.","DOI":"10.1109\/CCECE.2016.7726704"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"2388","DOI":"10.1109\/TGRS.2012.2211366","article-title":"Bayesian Wavelet Shrinkage with Heterogeneity-Adaptive Threshold for SAR images despeckling based on Generalized Gamma Distribution","volume":"51","author":"Li","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","unstructured":"Rajesh, M.R., Mridula, S., and Mohanan, P. (2016, January 22\u201325). Speckle Noise Reduction in Images using Wiener Filtering and Adaptive Wavelet Thresholding. Proceedings of the 2016 IEEE Region 10 Conference (TENCON), Singapore."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1260","DOI":"10.1109\/TIP.2002.804276","article-title":"Speckle reducing anisotropic diffusion","volume":"11","author":"Yu","year":"2002","journal-title":"IEEE Trans. Image Process."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"1543","DOI":"10.1016\/j.procs.2018.05.118","article-title":"Speckle noise reduction of ultrasound images using BFO cascaded with wiener filter and discrete wavelet transform in homomorphic region","volume":"132","author":"Dass","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_41","first-page":"589","article-title":"A new SAR image despeckling using directional smoothing filter and method noise thresholding","volume":"21","author":"Singh","year":"2019","journal-title":"Eng. Sci. Technol. Int. J."},{"key":"ref_42","first-page":"1587","article-title":"Speckle noise reduction in ultrasound images using a discrete wavelet transform-based image fusion technique","volume":"26","author":"Choi","year":"2015","journal-title":"Biomed. Mater. Eng."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3025","DOI":"10.1109\/TGRS.2015.2510161","article-title":"A SAR Image Despeckling Method Based on Two-Dimensional S Transform Shrinkage","volume":"54","author":"Gao","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"671","DOI":"10.1016\/j.asoc.2018.12.030","article-title":"Speckle noise removal in SAR images using Multi-Objective PSO (MOPSO) algorithm","volume":"76","author":"Sivaranjania","year":"2019","journal-title":"Appl. Soft Comput."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1397","DOI":"10.1109\/TPAMI.2012.213","article-title":"Guided image filtering","volume":"35","author":"He","year":"2013","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Saevarsson, B.B., Sveinsson, J.R., and Benediktsson, J.A. (2007, January 23\u201328). Combined Wavelet and Curvelet Denoising of SAR Images. Proceedings of the 2007 IEEE International Geoscience and Remote Sensing Symposium, Barcelona, Spain.","DOI":"10.1109\/IGARSS.2007.4422841"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"2324","DOI":"10.1109\/TIP.2008.2006658","article-title":"Multiresolution Bilateral Filtering for Image Denoising","volume":"17","author":"Zhang","year":"2008","journal-title":"IEEE Trans. Image Process."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1918","DOI":"10.1109\/TIP.2005.854492","article-title":"No-reference Quality Assessment Using Natural Scene Statistics: JPEG2000","volume":"14","author":"Sheikh","year":"2005","journal-title":"IEEE Trans. Image Process."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1007\/s11859-010-0212-y","article-title":"An image denoising method based on multiscale wavelet thresholding and bilateral filtering","volume":"15","author":"Wenxuan","year":"2010","journal-title":"Wuhan Univ. J. Nat. Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1109\/TPAMI.1982.4767223","article-title":"A model for radar images and its application to adaptive digital filtering of multiplicative noise","volume":"PAMI-4","author":"Frost","year":"1982","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1109\/TPAMI.1980.4766994","article-title":"Digital image enhancement and noise filtering by use of local statistics","volume":"PAMI-2","author":"Lee","year":"1980","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"5199","DOI":"10.1109\/TIP.2016.2605302","article-title":"The bitonic filter: Linear filtering in an edge-preserving morphological framework","volume":"25","author":"Treece","year":"2016","journal-title":"IEEE Trans. Image Process."},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Farbman, Z., Fattal, R., Lischinski, D., and Szeliski, R. (2008). Edge-preserving decomposition for multi-scale tone and detail manipulation. ACM Trans. Graph., 27.","DOI":"10.1145\/1399504.1360666"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Zhu, L., Fu, C.-W., Brown, M.S., and Heng, P.-A. (2017, January 21\u201326). A non-local low-rank framework for ultrasound speckle reduction. Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, Honolulu, HI, USA.","DOI":"10.1109\/CVPR.2017.60"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"345","DOI":"10.1109\/TIP.2014.2371244","article-title":"Anisotropic diffusion filter with memory based on speckle statistics for ultrasound images","volume":"24","year":"2015","journal-title":"IEEE Trans. Image Process."},{"key":"ref_56","unstructured":"Hyunho, C., and Jechang, J. (2018, January 7\u20139). Speckle noise reduction in ultrasound images using SRAD and guided filter. Proceedings of the International Workshop on Advanced Image Technology, Chiang Mai, Thailand."},{"key":"ref_57","unstructured":"(2018, December 30). Jet Propulsion Laboratory, Available online: https:\/\/photojournal.jpl.nasa.gov\/catalog\/PIA01763."},{"key":"ref_58","unstructured":"(2018, December 30). Dataset of Standard 512X512 Grayscale Test Images. Available online: http:\/\/decsai.ugr.es\/cvg\/CG\/base.htm."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Crow, F. (,  1984). Summed-area tables for texture mapping. Proceedings of the 11th Annual Conference on Computer Graphics and Interactive Techniques, New York, NY, USA.","DOI":"10.1145\/800031.808600"},{"key":"ref_60","unstructured":"Elad, M., and Ahalon, M. (2006, January 17\u201322). Image denoising via learned dictionaries and sparse representation. Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, New York, NY, USA."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/10\/1184\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T12:53:22Z","timestamp":1760187202000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/10\/1184"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,5,18]]},"references-count":60,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2019,5]]}},"alternative-id":["rs11101184"],"URL":"https:\/\/doi.org\/10.3390\/rs11101184","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,5,18]]}}}