Multiscale Region-Level VHR Image Change Detection via Sparse Change Descriptor and Robust Discriminative Dictionary Learning

Figure 2

A toy example for estimating the probability maps. (a)–(d) Image , image , ground truth (GT) image that is superposed on with red, and training mask (TM) image with red and blue denote the labeled changed and unchanged pixels, respectively. (e)–(g) The estimated coarse probability maps () by KNN and (h) the weighted sum of them, . (i)–(k) The refined probability maps () and (l) the weighted sum of them, .

(a) I

(b) J

(c) GT

(d) TM

(e)

(f)

(g)

(h)

(i)

(j)

(k)

(l)