Skip to main content
EURASIP Journal on Advances in Signal Processing
Figure 2 | EURASIP Journal on Advances in Signal Processing

Figure 2

From: A learning-based target decomposition method using Kernel KSVD for polarimetric SAR image classification

Figure 2

Decomposition performance based on scattering mechanisms, KSVD and Kernel KSVD. The blue, green and yellow points represent the nonlinear feature in the input space. The 〈 x, y, z 〉 is some fixed coordinate system based on scattering me chanisms and 〈 d1, d2, d3 〉 is the learned coordinate system based on KSVD and Kernel KSVD algorithm. The red arrows represent the projections of the yellow points on different decomposition bases. (a) Decomposition based on scattering mechanisms, 〈x, y, z 〉 is orthogonal. (b) Decomposition based on KSVD algorithm, 〈d1, d2, d3 〉 is linear towards the direction of feature points. (c) Decomposition based on proposed the Kernel KSVD algorithm, 〈 d1, d2, d3 〉 is a curvilinear coordinate that goes along the flow of feature points.

Back to article page