Journals / Harita Dergisi / 2018 / Cilt: 84 - Sayı: 160

Image Segmentation Approaches in Object-Based Image Analysis and Analysis of Segmentation Quality

Nesne Tabanlı Görüntü Analizinde Görüntü Bölütleme Yaklaşımları ve Bölütleme Kalitesinin Analizi

Pages
12–23
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Moreover, some guidelines and considerations are presented for researchers to conduct segmentation properly focusing on some crucial research issues.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In recent years, with the increase in the amount of satellite images with high spatial resolution, the extraction of information from these images containing high spectral heterogeneity has been an important subject of research.
📊
Key Findings & Data:This study provides detailed information about the image segmentation algorithms, parameter selection strategies and image segmentation quality studies with literature review.
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Conclusion & Impact:Moreover, some guidelines and considerations are presented for researchers to conduct segmentation properly focusing on some crucial research issues.
🔬Design:Review & Systematic Survey
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In recent years, with the increase in the amount of satellite images with high spatial resolution, the extraction of information from these images containing high spectral heterogeneity has been an important subject of research. Conventional approaches are deficient to extract information from these images. Object-based image analysis (OBIA) has emerged as a new paradigm that is effectively used in the analysis of high-resolution remote sensing images. The first and basic step of NTGA is the image segmentation that is applied to create image objects. The shape, size, and spectral properties of the objects are determined by the segmentation approach. Selection of appropriate method and its parametres is crucial for optimal image segmentation before the image classification or feature extraction stages. This study provides detailed information about the image segmentation algorithms, parameter selection strategies and image segmentation quality studies with literature review. Moreover, some guidelines and considerations are presented for researchers to conduct segmentation properly focusing on some crucial research issues.

Özet

Son yıllarda yüksek mekânsal çözünürlüklü uydu görüntü miktarındaki artış ile birlikte yüksek spektral heterojenlik içeren bu görüntülerden bilgi çıkarımı önemli bir araştırma konusu olmuştur. Bu görüntülerden bilgi çıkarabilmek için geleneksel yaklaşımların kullanımı yeterli olmamaktadır. Nesne tabanlı görüntü analizi (NTGA), yüksek çözünürlüklü uzaktan algılanmış görüntülerinin analizinde etkin şekilde kullanılan yeni bir paradigma olarak ortaya çıkmıştır. NTGA’nın ilk ve en temel adımını görüntü nesneleri oluşturmaya yarayan görüntü bölütleme adımı oluşturmaktadır. Nesnelerin şekli, boyutu ve spektral özellikleri bölütleme yaklaşımına bağlı olarak belirlenmektedir. Optimum görüntü bölütleme için gerekli yöntem ve parametre seçimi, görüntü sınıflandırması veya özellik çıkarımı işleminden önce karar verilmesi gereken çok önemli hususlardır. Bu çalışma, NTGA alanında kullanılan görüntü bölütleme algoritmaları, parametre seçim stratejileri ve görüntü bölütleme kalitesi konusunda yapılan çalışmalar hakkında detaylı bilgiler ve literatür taraması sunmaktadır. Görüntü bölütleme işlemini doğru şekilde gerçekleştirmek için araştırmacılara rehberlik edecek ve uygulamada dikkat edilmesi gereken kritik hususları içeren değerlendirmeler ayrıca sunulmuştur.

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Cite This Article

TONBUL, H., KAVZOĞLU, T. (2018). Image Segmentation Approaches in Object-Based Image Analysis and Analysis of Segmentation Quality. Harita Dergisi, Cilt: 84 - Sayı: 160, 12–23. https://ajindex.com/articles/160134

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