Fuzzy clustering algorithms incorporating local information for change detection in remotely sensed images

Mishra, Niladri Shekhar; Ghosh, Susmita; Ghosh, Ashish

doi:10.1016/j.asoc.2012.03.060

Cited by 76 publications

(47 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Önerilen yaklaşımın etkinliğini irdeleyebilmek için daha önce birçok değişim saptama çalışmasında kullanılan optik görüntülerden oluşan Sardinia ve Mexico veri setleri kullanılmıştır [4,12,15,16,22]. Veri setleri birbirine kaydedilmiş ve histogramlarının incelenmesi neticesinde radyometrik düzeltme yapılmasına gerek duyulmamıştır.…”

Section: Bulgular Ve Tartişmaunclassified

“…Mishra ve ark. 2012 yılında orman yangını neticesinde oluşan tahribatın önerdikleri kontrolsüz değişim yaklaşımı ile belirlenebileceğini göstermişlerdir [15]. Ghosh ve ark.…”

Section: Introductionunclassified

“…Gaussian karışım modelleri kümelenecek veriye, küme sayısı kadar normal dağılım modeli uydurmaktadır. Kontrolsüz değişim saptama tekniklerinin performanslarının incelenmesi için toplam hata ve toplam hata oranı en sık tercih edilen metriklerden olmuştur [10][11][12][13]15]. Bu çalışmada, bu kriterlere ek olarak ortalama karesel hata, tepe gürültü sinyal oranı, yapısal benzerlik indeksi ve evrensel kalite indekside kullanılmıştır.…”

Section: Introductionunclassified

See 2 more Smart Citations

Afet Yöneti̇mi̇nde Opti̇k Görüntüler İçi̇n Dalgacik Dönüşümü Ve Gaussian Karişim Modelleri̇ Tabanli Yeni̇ Bi̇r Deği̇şi̇m Saptama Yaklaşimi

Atasever

2018

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

View full text Add to dashboard Cite

ÖZOrman yangını, taşkın gibi felaketler hem ülkemizin hem de dünyanın en önemli problemleri arasındadır Afet sonrası alansal rehabilitasyon işlemlerinin hızla yapılabilmesi için zarar gören alanların hızlı ve yüksek doğrulukla belirlenebilmesi gerekmektedir. Bu çalışmada, optik görüntüler için tasarlanmış, yangın ve sel gibi afetler sonrasında hasar gören alanların tespit edilmesine yönelik dalgacık dönüşümü ve Gaussian karışım modelleri temelli yeni bir yaklaşım önerilmiştir. Sunulan yaklaşımın ilk aşamasında, afet öncesi ve sonrasına ait görüntülerin standart ve logaritmik fark görüntüleri hesaplanır. İkinci aşamada standart fark görüntüsüne medyan filtre, logaritmik fark görüntüsüne wiener filtre uygulanır. Ardından bu görüntüler dalgacık dönüşümü ile birleştirilir. Son aşamada ise birleştirilmiş görüntü Gaussian karışım modelleri ile kümelenir ve böylelikle afet nedeniyle zarar gören alanlar tespit edilmiş olur. Yaklaşımın etkinliği gerçek afetler neticesinde ortaya çıkan Sardinia ve Mexico veri setleri kullanılarak irdelenmiştir. Önerilen yaklaşımın performansı toplam hata ve toplam hata oranı kriterlerine ek olarak ortalama karesel hata, tepe gürültü sinyal oranı, yapısal benzerlik indeksi ve evrensel kalite indeksi metrikleri ile incelenmiş ve başarısı ortaya koyulmuştur.Anahtar Kelimeler: Afet, Değişim Saptama, Dalgacık Dönüşümü, Gaussian Karışım Modelleri A NEW CHANGE DETECTION APPROACH BASED ON WAVELET TRANSFORMATION AND GAUSSIAN MIXTURE MODELS FOR OPTICAL IMAGERY IN DISASTER MANAGEMENT ABSTRACTDisasters such as forest fires and floods are among most important problems of both our country and the world. In order to be able to perform rapid rehabilitation processes after disaster, damaged areas should be determined with high accuracy quickly. In this study, a new approach, designed for optical images, based on wavelet transform and Gaussian mixture models is proposed for detection of damaged areas after disasters such as fire and flood. In the first step of the presented approach, standard and logarithmic difference images from images belonging before and after disaster are calculated. Second, median filter to standard difference image and wiener filter to logarithmic difference image are applied, respectively. After that, these images are fused with wavelet transformation. Lastly, fused image is clustered with Gaussian mixture models and thus the areas damaged by the disasters are identified. The effectiveness of the approach was explored using Sardinia and Mexico data sets resulting from real disasters. The performance of the proposed approach has been investigated and its success has been shown with the mean squared error, peak signal to noise ratio, structural similarity index and universal quality index metrics, in addition to the total error and total error rate criteria.

show abstract

Section: Bulgular Ve Tartişmaunclassified

Section: Introductionunclassified

See 1 more Smart Citation

Afet Yöneti̇mi̇nde Opti̇k Görüntüler İçi̇n Dalgacik Dönüşümü Ve Gaussian Karişim Modelleri̇ Tabanli Yeni̇ Bi̇r Deği̇şi̇m Saptama Yaklaşimi

Atasever

2018

Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi

View full text Add to dashboard Cite

show abstract

“…Since the pixels are highly correlated with their neighbors in image space (spatial domain), incorporation of local information enhances the performance of the algorithms. So they introduced a new technique for incorporation of local information (Mishra et al, 2012). Different change detectors produce different results since they handle the data differently.…”

Section: Introductionmentioning

confidence: 99%

Urban Expansion Monitoring Using Satellite Images by Means of Decision Level Fusion of Fuzzy Change Detectors

Mahmoudi

Saradjian

Esmaeily

et al. 2013

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:This study investigates urban expansion using satellite images by means of decision level fusion of two different fuzzy change detectors. The aim of this study is taking the advantage of effects of various change detection techniques. These techniques are differentiated by the way they use the dataset which their fusion could lead us to gain complementary outputs and ultimately achieve higher accuracy in change detection. This study focuses on the use of this framework specifically for urban region expansion monitoring. Here outputs of two fuzzy change detectors based respectively on post classification comparison and spectral-temporal combined analysis methods of multi-temporal ASTER images are fused by using Sugeno fuzzy integral operator. Accuracy assessment that has been done by available land cover maps for fuzzy post classification comparison combined fuzzy spectraltemporal analysis and their combination technique has shown improvement of change detection accuracy over each single fuzzy change detector in urban expansion application.

show abstract

“…One of the most popular threshold methods was proposed by Bruzzone, where the difference image is supposed as mixture Gaussian model and the Bayes rule for minimum error is adopted to calculate the threshold using expectation maximum (EM) algorithm (Bruzzone and Prieto, 2000). Due to many false alarms existing in the change map obtained by threshold, the spatial information was introduced by some advanced models, such as Markov random model (Gu et al, 2015;Subudhi et al, 2016), , support vector machine (Nemmour and Chibani, 2006), artificial neural network (Wang et al, 2015;Xu et al, 2015), wavelet transform (Celik and Ma, 2011), active contour model (Hao et al, 2014;Li et al, 2015) and fuzzy c-means clustering (FCM) algorithm (Ghosh et al, 2011;Krinidis and Chatzis, 2010;Mishra et al, 2012). The ranges of pixel gray values in difference image belonging to the changed and unchanged clusters often have overlap, FCM has robust characteristics for ambiguity and provides an appropriate choice to identify them by using fuzzy set information (Ghosh et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Change Detection by Fusing Advantages of Threshold and Clustering Methods

Tan

Hao

2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

View full text Add to dashboard Cite

ABSTRACT:In change detection (CD) of medium-resolution remote sensing images, the threshold and clustering methods are two kinds of the most popular ones. It is found that the threshold method of the expectation maximum (EM) algorithm usually generates a CD map including many false alarms but almost detecting all changes, and the fuzzy local information c-means algorithm (FLICM) obtains a homogeneous CD map but with some missed detections. Therefore, we aim to design a framework to improve CD results by fusing the advantages of threshold and clustering methods. Experimental results indicate the effectiveness of the proposed method.

show abstract

Fuzzy clustering algorithms incorporating local information for change detection in remotely sensed images

Cited by 76 publications

References 34 publications

Afet Yöneti̇mi̇nde Opti̇k Görüntüler İçi̇n Dalgacik Dönüşümü Ve Gaussian Karişim Modelleri̇ Tabanli Yeni̇ Bi̇r Deği̇şi̇m Saptama Yaklaşimi

Afet Yöneti̇mi̇nde Opti̇k Görüntüler İçi̇n Dalgacik Dönüşümü Ve Gaussian Karişim Modelleri̇ Tabanli Yeni̇ Bi̇r Deği̇şi̇m Saptama Yaklaşimi

Urban Expansion Monitoring Using Satellite Images by Means of Decision Level Fusion of Fuzzy Change Detectors

Change Detection by Fusing Advantages of Threshold and Clustering Methods

Contact Info

Product

Resources

About