Figure 1
From: Dempster–Shafer fusion of multisensor signals in nonstationary Markovian context
Unsupervised segmentation of multisensor noisy image 1. (a) Original class image X = x. (b) First sensor observed image Y1 = y1. (c) Second sensor observed image Y2 = y2. (d) Image restoration using K-Means, error ratio τK-Means = 39.4%. (e) Image MPM restoration using HMCs, error ratio τHMC = 16.5%. (f) Image MPM restoration using evidential HMCs, error ratio τEHMC = 11.1%. (g) MPM estimation of the auxiliary process U1 according to evidential HMCs. (h) Image MPM restoration using multisensor stationary HMCs, error ratio τMS-HMC = 12%. (i) Estimation of the underlying U2 process according to multisensor stationary HMCs, error ratio τMS-HMC = 0.1%. (j) Image MPM restoration using multisensor nonstationary HMCs, error ratio τMN-HMC = 7.9%. (k) MPM estimation of the auxiliary process U1 according to multisensor nonstationary HMCs. (l) Estimation of the underlying U2 process according to multisensor nonstationary HMCs, error ratio τMN-HMC = 0.1%.