"Change detection using remotely sensed images has many applications, such as urban monitoring, land-cover change analysis, and disaster management. This work investigates two-dimensional change detection methods. The existing methods in the literature are grouped into four categories: pixel-based, transformation-based, texture analysis-based, and structure-based. In addition to testing existing methods, four new change detection methods are introduced: fuzzy logic-based, shadow detection-based, local feature-based, and bipartite graph matching-based. The latter two methods form the basis for a structural analysis of change detection. Three thresholding algorithms are compared, and their effects on the performance of change detection methods are measured. These tests on existing and novel change detection methods make use of a total of 35 panchromatic and multi-spectral Ikonos image sets. Quantitative test results and their interpretations are provided." Read more... Introduction -- Pixel-Based Change Detection Methods -- Transformation-Based Change Detection Methods -- Texture analysis based change detection methods -- Structure-Based Change Detection Methods -- Fusion of Change Detection Methods -- Experiments -- Final Comments
Author(s): Murat İlsever; Cem Ünsalan
Series: SpringerBriefs in computer science
Publisher: Springer
Year: 2012
Language: English
Pages: 77
City: London ; New York
Tags: Приборостроение;Обработка сигналов;
Cover......Page 1
Two-Dimensional Change
Detection Methods......Page 3
Preface......Page 5
Acknowledgments......Page 7
Contents......Page 8
8 Final Comments......Page 10
1.2 Layout of the Study......Page 13
References......Page 14
2.1 Image Differencing......Page 15
2.2 Image Rationing......Page 19
2.3 Image Regression......Page 20
2.4 Change Vector Analysis......Page 22
2.5 Median Filtering-Based Background Formation......Page 24
2.6 Pixelwise Fuzzy XOR Operator......Page 25
References......Page 29
3.1 Principal Component Analysis......Page 30
3.2 Kauth-Thomas Transformation......Page 32
3.3 Vegetation Index Differencing......Page 34
3.4 Time-Dependent Vegetation Indices......Page 36
3.5 Color Invariants......Page 37
References......Page 40
4.1 Gray Level Co-occurrence Matrix......Page 42
4.2 Entropy......Page 45
References......Page 46
5.1 Edge Detection......Page 47
5.3 Matched Filtering......Page 48
5.4 Mean Shift Segmentation......Page 49
5.5 Local Features......Page 51
5.6 Graph Matching......Page 52
5.7 Shadow Information......Page 54
References......Page 57
6.1 Fusion Methodology......Page 58
6.3 Inter-Category Level Fusion......Page 59
7.2 Performance Tests......Page 62
7.2.1 Pixel-Based Change Detection Methods......Page 66
7.2.3 Texture-Based Change Detection Methods......Page 67
7.2.4 Comparison of Thresholding Algorithms......Page 68
7.2.5 Structure-Based Change Detection Methods......Page 70
7.2.6 Fusion of Change Detection Methods......Page 73
References......Page 75
