Simultaneous registration and change detection in multitemporal, very high resolution remote sensing data
Summary (3 min read)
1. Introduction
- The current generation of space-borne and airborne sensors are generating nearly continuous streams of massive multi-temporal high resolution remote sensing data.
- Most remote sensing and GIS software still employ semi-automated registration procedures when it comes to very large, multispectral, very high resolution satellite data [17, 7].
- Among the various recently proposed methods, those based on Markov Random Fields [8, 24, 1], kernels [2, 26] and neural networks [22, 23] have gained important attention.
- Focusing on man-made object change detection [4, 20] in urban and peri-urban regions, several approaches have been proposed based on very high resolution optical and radar data [19, 23, 6, 20].
2.1. MRF formulation
- The authors have designed and built an MRF model over two different graphs of the same dimensions.
- The interaction between the two graphs is performed by the similarity cost which connect the registration with the change detection terms.
- Each graph is superimposed on the image [9] and therefore every node of the graph acts and depends on a subset of pixels in the vicinity (depending on the chosen interpolation strategy).
- In particular, the dimensions of the graph are related to the image dimensions forming a trade off between accuracy and computational complexity.
- Ech and the authors couple the two different graphs to one.
2.2. The Registration Energy Term
- The goal of image registration is to define a transformation map T which will project the source image to the target image.
- The energy formulation for the registration comprises of a similarity cost (that seeks to satisfy the equation 2) and a smoothness penalty on the deformation domain.
- The similarity cost depends on the presence of changes and will be subsequently defined.
- The smoothness term penalises neighbouring nodes that have different displacement labels, depending on the distance of the labelled displacements.
2.3. The Change Detection Energy Term
- The goal of the change detection term is to estimate the changed and unchanged image regions.
- The authors employ two different labels in order to address the change detection problem lcp ∈ [0, 1].
- The energy formulation for the change detection corresponds to a smoothness term which penalizes neighbouring nodes with different change labels.
2.4. Coupling the Energy Terms
- The coupling between change detection and registration is achieved through the interconnection between the two graphs.
- These two terms are integrated as in (equation 5) which simply uses a fixed cost in the presence of changes and the image matching cost in their absence.
- With a slight abuse of notation the authors consider a node with an index p ∈ G (they recall that the two graphs are identical) corresponding to the same node throughout the two graphs (Greg, Gch).
- In such a setting, optimizing an objective function seeking similarity correspondences is not meaningful and deformation vectors should be the outcome of the smoothness constraint on the displacement space.
- Let us consider that this value is known and that it is independent from the image displacements, so the authors can distinguish the regions that have been changed.
2.5. Optimization
- There are several techniques for the minimization of an MRF model which can be generally summarised into those based on the message passing and those on graph cut methods.
- The first category is related to the linear programming relaxation [14].
- The optimization of the implementation is performed by FastPD which is based on the dual theorem of linear programming [15, 16].
3. Implementation
- Concerning the image, iteratively different levels of Gaussian image pyramids are used.
- In all their experiments, 2 image and 3 grid levels were found adequate for the very high resolution satellite data.
- Regarding the label space, a search for possible displacements along 8 directions (x, y and diagonal axes) is performed, while the change labels are always two and correspond to change or no change description.
- Depending on the parameter label factor the values of registration labels change towards the optimal ones.
- One of the problems in traditional change detection techniques, is that change in intensities does not directly mean semantic change.
4.1. Dataset
- The developed framework was applied to several pairs of multispectal VHR images from different satellite sensors (i.e., Quickbird and WorldView-2).
- The multi-temporal dataset covers approximately a 9 km2 region in the East Prefecture of Attica in Greece.
- The dataset is quite challenging both due to its size and the pictured complexity derived from the different acquisition angles.
- For the quantitative evaluation the ground truth was manually collected and annotated after an attentive and laborious photointerpretation done by an expert.
4.2. Experimental Results
- Regarding the evaluation for the man-made change detection task, experimental results after the application of the developed method are shown in Figure 3 and Figure 4.
- In particular, in Figure 3 the detected changes are shown with a red color while the ground truth polygons are shown with green.
- The behaviour of the developed method can be further observed in Figure 5, where certain examples with True Positives, False Negatives and False Positives cases are presented.
- The selected metric affects, also, the computational time significantly.
5. Conclusions
- Developed and validated a novel framework which address concurrently the registration and change detection tasks in very high resolution multispectral multitemporal optical satellite data.the authors.
- The developed method is modular, scalable and metric free.
- The formulation exploits a decomposed interconnected graphical model formulation where registration similarity constraints are relaxed in the presence of change detection.
- The framework was optimized for the detection of changes related to man-made objects in urban and peri-urban environments.
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Citations
319 citations
200 citations
Cites background from "Simultaneous registration and chang..."
...A few of them investigated the possibility of using very high resolution (VHR) images for 2D CD in a finer level (Bouziani et al., 2010; Brunner et al., 2010; Huang et al., 2014; Košecka, 2012; Vakalopoulou et al., 2015)....
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142 citations
Cites methods from "Simultaneous registration and chang..."
...Unsupervised methods have been used for change detection in many different ways (Hussain et al., 2013; Vakalopoulou et al., 2015; Liu et al., 2019)....
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103 citations
Cites background from "Simultaneous registration and chang..."
...Change detection is a non-trivial problem as the accuracy of a method is highly influenced by registration errors [2] and illumination changes that do not really correspond to semantic changes....
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66 citations
Cites background or methods from "Simultaneous registration and chang..."
...Following the notations of [6] and [55], the first graph, Greg, involved nodes where the labels corresponded to deformation vectors from the registration process, i....
[...]
...1) the registration (Vpq,reg(l reg p , l reg q )) and change detection (Vpq,ch(l p , l ch q )) pairwise terms followed the same formulation as in [6] and [55] and penalized neighboring nodes...
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...In particular, the formulation of [6] and [55], was extended...
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References
133 citations
"Simultaneous registration and chang..." refers background in this paper
...Focusing on man-made object change detection [4, 20] in urban and peri-urban regions, several approaches have been proposed based on very high resolution optical and radar data [19, 23, 6, 20]....
[...]
100 citations
"Simultaneous registration and chang..." refers methods in this paper
...Among the various recently proposed methods, those based on Markov Random Fields [8, 24, 1], kernels [2, 26] and neural networks [22, 23] have gained important attention....
[...]
97 citations
"Simultaneous registration and chang..." refers background in this paper
...Focusing on man-made object change detection [4, 20] in urban and peri-urban regions, several approaches have been proposed based on very high resolution optical and radar data [19, 23, 6, 20]....
[...]
89 citations
"Simultaneous registration and chang..." refers background in this paper
...Focusing on man-made object change detection [4, 20] in urban and peri-urban regions, several approaches have been proposed based on very high resolution optical and radar data [19, 23, 6, 20]....
[...]
81 citations
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Frequently Asked Questions (2)
Q2. What are the future works in "Simultaneous registration and change detection in multitemporal, very high resolution remote sensing data" ?
The integration of prior knowledge regarding texture and geometric features is currently under development and a gpu implementation is among the future perspectives as well.