پیوندهای مفید
اخبار و اعلانات
آمار
| تعداد نشریات | 13 |
| تعداد شماره‌ها | 200 |
| تعداد مقالات | 2,008 |
| تعداد مشاهده مقاله | 2,680,135 |
| تعداد دریافت فایل اصل مقاله | 1,937,344 |
انتخاب ترکیب بهینه ویژگی‌های بافتی به‌روش ژنتیک، به‌منظور طبقه‌بندی تصاویر با قدرت تفکیک مکانی بالا | ||
| پژوهش های سنجش از دور و اطلاعات مکانی | ||
| مقالات آماده انتشار، پذیرفته شده، انتشار آنلاین از تاریخ 16 خرداد 1403 | ||
| نوع مقاله: مقاله پژوهشی | ||
| شناسه دیجیتال (DOI): 10.22061/jrsgr.2024.10880.1065 | ||
| نویسنده | ||
| حامد عاشوری* | ||
| گروه مهندسی نقشه‌برداری، واحد قزوین، دانشگاه آزاد اسلامی، قزوین، ایران | ||
| تاریخ دریافت: 16 اردیبهشت 1403، تاریخ بازنگری: 13 تیر 1403، تاریخ پذیرش: 16 خرداد 1403 | ||
| کلیدواژه‌ها | ||
| طبقه‌بندی تصویر؛ کمی‌سازی بافت؛ انتخاب ویژگی؛ الگوریتم ژنتیک؛ تصویر با قدرت تفکیک مکانی بالا | ||
| عنوان مقاله [English] | ||
| Improving Classification Accuracy of High Spatial Resolution Images by Using Texture Quantization and Genetic Feature Selection | ||
| نویسندگان [English] | ||
| H. Ashoori | ||
| Department of Geomatics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran | ||
| کلیدواژه‌ها [English] | ||
| Classification, Feature Selection, Genetic Algorithm, High Spatial Resolution Image, Texture Quantization | ||
| مراجع | ||
|
[1] Fauvel M, Benediktsson JóA, Chanussot J, Sveinsson JR. Spectral and Spatial Classification of Hyperspectral Data Using SVMs and Morphological Profiles. IEEE Transactions on Geoscience and Remote Sensing. 2008 Nov;46(11):3804–14.
[2] Gaetano R, Scarpa G, Poggi G. Hierarchical Texture-Based Segmentation of Multiresolution Remote-Sensing Images. IEEE Transactions on Geoscience and Remote Sensing. 2009 Jul;47(7):2129–41.
[3] Puig D, Angel Garcia M. Automatic texture feature selection for image pixel classification. Pattern Recognition. 2006 Nov;39(11):1996–2009.
[4] Lin CH, Chen HY, Wu YS. Study of image retrieval and classification based on adaptive features using genetic algorithm feature selection. Expert Systems with Applications. 2014 Nov;41(15):6611–21.
[5] Welikala RA, Fraz MM, Dehmeshki J, Hoppe A, Tah V, Mann S, et al. Genetic algorithm-based feature selection combined with dual classification for the automated detection of proliferative diabetic retinopathy. Computerized Medical Imaging and Graphics. 2015 Jul; 43:64–77.
[6] Ruiz LA, Fdez-Sarría A, Recio JA. Texture feature extraction for classification of remote sensing data using wavelet decomposition: a comparative study. 20th ISPRS Congress. 2004; Vol. 35. No. part B.
[7] Castleman KR. Digital Image Processing. Pearson; 1996.
[8] Theodoridis S, Konstantinos Koutroumbas. Pattern recognition. Amsterdam Elsevier/Acad. Press [20]11.
[10] Laws, K. Textured Iage Segmentation. 1980; Ph.D Dissertation, University of South California.
[11] Pratt WK. Digital image processing: PIKS Scientific inside. Hoboken, N.J.: Wiley-Interscience; 2007.
[12] Yu S, De Backer S, Scheunders P. Genetic feature selection combined with composite fuzzy nearest neighbor classifiers for hyperspectral satellite imagery. Pattern Recognition Letters. 2002 Jan;23(1-3):183–90.
[13] Feature selection using genetic algorithm for classification of schizophrenia using fMRI data. Journal of Artificial Intelligence and Data Mining. 2015;3(1).
[14] Singh DAAG, Leavline EJ, Priyanka R, Priya PP. Dimensionality Reduction using Genetic Algorithm for Improving Accuracy in Medical Diagnosis. International Journal of Intelligent Systems and Applications. 2016 Jan 8;8(1):67–73.
[15] Liang Y, Zhang M, Browne WN. Image feature selection using genetic programming for figure-ground segmentation. 2017; Engineering Applications of Artificial Intelligence, Volume 62: 96-108.
[16] http://www.grss-ieee.org/community/technical-committees/data-fusion/, 2014 IEEE GRSS Data Fusion Contest. Online.
[17] Boyd DS, Foody GM, Ripple WJ. Evaluation of approaches for forest cover estimation in the Pacific Northwest, USA, using remote sensing. Applied Geography. 2002 Oct;22(4):375–92.
[18] Joshi C, Leeuw JD, Skidmore AK, Duren IC van, van Oosten H. Remotely sensed estimation of forest canopy density: A comparison of the performance of four methods. International Journal of Applied Earth Observation and Geoinformation. 2006 Jun;8(2):84–95.
[19] Cross A, Settle JJ, Drake N, R. Päivinen. Subpixel measurement of tropical forest cover using AVHRR data. International Journal of Remote Sensing. 1991 May 1;12(5):1119–29.
[20] Souza C. Mapping Forest degradation in the Eastern Amazon from SPOT 4 through spectral mixture models. Remote Sensing of Environment. 2003 Nov 15;87(4):494–506.
[21] Lévesque J, King DJ. Spatial analysis of radiometric fractions from high-resolution multispectral imagery for modelling individual tree crown and forest canopy structure and health. Remote Sensing of Environment. 2003 Apr;84(4):589–602.
[22] Akbari D, Akbari V. Object‑based classification of hyperspectral images based on weighted genetic algorithm and deep learning model. Applied Geomatics. 2023; 15, 227–238.
[23] Akbari D, Rokni K. Spectral-spatial classification of hyperspectral images based on nonlinear principal component analysis and deep learning models. International Journal of Remote Sensing. 2023; Volume 23.
[24] Zhu W, Yang X, Liu R, Zhao C. A new feature extraction algorithm for measuring the spatial arrangement of texture Primitives: Distance coding diversity. International journal of applied earth observation and geoinformation. 2024 Mar 1; 127:103698–8. | ||
|
آمار تعداد مشاهده مقاله: 34 |
||