Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Adaptive Local Structure Consistency based Heterogeneous Remote Sensing
  Change Detection   Change detection of heterogeneous remote sensing images is an important and
challenging topic in remote sensing for emergency situation resulting from
nature disaster. Due to the different imaging mechanisms of heterogeneous
sensors, it is difficult to directly compare the images. To address this
challenge, we explore an unsupervised change detection method based on adaptive
local structure consistency (ALSC) between heterogeneous images in this letter,
which constructs an adaptive graph representing the local structure for each
patch in one image domain and then projects this graph to the other image
domain to measure the change level. This local structure consistency exploits
the fact that the heterogeneous images share the same structure information for
the same ground object, which is imaging modality-invariant. To avoid the
leakage of heterogeneous data, the pixelwise change image is calculated in the
same image domain by graph projection. Experiment results demonstrate the
effectiveness of the proposed ALSC based change detection method by comparing
with some state-of-the-art methods.

25
The categories of this paper are: patt-sol
31
The categories of this paper are: ao-sci
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
29
The categories of this paper are: funct-an
23
The categories of this paper are: solv-int
17
The categories of this paper are: q-fin
0
The categories of this paper are: hep-ph
37
The categories of this paper are: supr-con
27
The categories of this paper are: comp-gas
26
The categories of this paper are: bayes-an
21
The categories of this paper are: adap-org
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
22
The categories of this paper are: chao-dyn