4-Component Scattering Power Decomposition with Phase Rotation of Coherency Matrix

Transcription

1 4-Component Scattering Power Decomposition with Phase Rotation o Coherency Matrix Gulab Singh*, Yoshio Yamaguchi and S.-E. Park Niigata University *g.singh@wave.ie.niigata-u.ac.jp

2 Outline Introduction: Scattering Power Decompositions and their problems Phase Rotation: Complex Unitary ransormation (CU) Conversion o 4- to 3-Component Scattering Power Decomposition Results Summary and Conclusions

3 Purpose: o decompose dierent scattering contributions Introduction (/6) POLSAR Data Applications: POLSAR image interpretation, classiication and segmentation, and scattering parameter inversion. S S = S HH HV S S HV VV Scattering Matrix S HV =S VH k = (/2) race {S[ψ]} Scattering Vector k p = (/ 2) [S HH + S VV, S HH - S VV, 2S HV ] t Pauli Matrices Group Pauli Scattering Vector [ ] MN M N k p k p i j Multi-looked Coherency Matrix Scattering Power Decompositions (natural/distributed targets)

4 Introduction (2/6) 2 4 * 2 2 * v d s Pd Ps Pv Freeman and Durden 3-Component Scattering Power Decomposition (3-CSPD) [] [] A. Freeman and S. L. Durden, ``A hree-component scattering model or polarimetric SAR data,`` IEEE GRS, Vol.36, No. 3, pp , May 998. ] [ ] [ ] [ v v d d s s with relection symmetry or natural distributed targets otal Power (P)= Surace Scattering Double Bounce Scattering Volume scattering + +

5 Introduction (3/6) 3-CSPD 4-CSPD = + [2] Y. Yamaguchi,. Moriyama, M. Ishido and H. Yamada, ``Four-Component Scattering Model or Polarimetric SAR Image Decomposition,`` IEEE GRS, Vol.43, No.8, pp , Aug Component Scattering power decomposition [2]-[3] helix scattering under with non-relection symmetry by proposing new matrices or volume scattering ] [ ] [ ] [ ] [ c c v v d d s s [3] Y. Yajima, Y. Yamaguchi, R. Sato and H. Yamada, ``POLSAR image analysis o wetlands using a modiied our-component scattering power decomposition,`` IEEE GRS, Vol.46, No.6, pp , June sin 2 ) p( cos 2 ) p( 2 ) p( 2 j j P = + Pd Ps Pv Pc + + d p v ) ( )] ( [ ] [ (Y4-)

6 Japan Sea (4/6) Freeman-Durden RGB Range Niigata University Optical Fully polarimetric errasar-x data April 2, 2 Y4-4-CSPD RGB Range Strong volume scattering [4]-[5] Misclassiication o man-made targets [5] [4] J. S. Lee and. L. Ainsworth, he eect o orientation angle compensation on coherency matrix and polarimetric target decompositions, IEEE GRS, vol. 49, no., pp.53-64, 2. [5] Y. Yamaguchi, A. Sato, W.-M. Boerner, R. Sato, and H. Yamada, Four-component scattering power decomposition with rotation o coherency matrix, IEEE GRS., vol. 49, no. 7, July 2.

7 Introduction (5/6) Pd Rotation o [] about line o sight [4]-[5] ' ' 3 23 cos 2 ' 33 sin 2 cos 2 sin 2 Rotation Matrix : Real Unitary ransormation ' ' ' cos 2 sin 2 2 ' 3 ' 2 22 ' 32 Determination o the rotation angle d 33 d 4-CSPD or the rotated matrix (Y4-R) sin 2 cos 2 [ ' ] s[ s ] d[ d ] v[ v ] c[ c ] [4] J. S. Lee and. L. Ainsworth, he eect o orientation angle compensation on coherency matrix and polarimetric target decompositions, IEEE GRS, vol. 49, no., pp.53-64, 2. [5] Y. Yamaguchi, A. Sato, W.-M. Boerner, R. Sato, and H. Yamada, Four-component scattering power decomposition with rotation o coherency matrix, IEEE GRS, vol. 49, no. 7, July 2. Y4- Y4-R Ps Pv Range

8 Volume Scattering 4-CSPD RGB Y4- Y4-R Beore rotation Introduction (6/6) Pd Ater rotation (RU) Range Ps Pv Max. Multi-looking 6x Min. -ve

9 Volume Scattering 4-CSPD RGB Y4- Y4-R Beore rotation Introduction (6/6) Pd Ater rotation (RU) Range Ps Pv Max. [5] Multi-looking 6x Min. -ve

10 Phase Rotation: Complex Unitary ransormation (/3)

11 CU(2/3) (ɸ) 23 (ɸ) has no imaginary part. his means no helix power in the 4- CSPD model.

12 Phase Rotation o [] : CU (3/3) Range Y3-CU Y4-R Y3-CU

13 (/4) Results Jammu and Kashmir Himachal ibet Delhi Rajasthan I N Madhya D Pradesh I A Gujarat Bhutan Y4- Bihar Maharashtra Y3-CU Y4-R ALOS-PALSAR Footprint ALOS- PALSAR SLC May 2, 27 Azimuth

14 Results : Eect o steep slope (2/4) Azimuth Pc in Y4- & Y4-R Pd Y4- Y4-R Y3-CU Ps Pv Multi-Looked actor: 6 x

15 Pd Ps (3/4) Pv Y4-R and Filtering Results : Eect o multi-looking Y3-CU Azimuth Multi-look 6x Multi-look 6x; and Lee ilter 7x7 Multi-look 2x2; and Lee ilter 7x7 Involved * + elements: 6/8 and θ Involved *(ɸ)+ elements: 5/8 and ɸ

16 Distribution o Power in % Distribution o Power in % Results (4/4).5.3 Pv-beore rotation Pv-ater complex rotation Pv-ater real rotation Multi-look 6x, and Lee ilter 7x Y4- Y4-R Y3-CU Pd Pc Ps Pv Multi-look 6x; and Lee ilter 7x Y4 Y3-CU Y4-R Pd Pc Ps Pv Multi-look 2x2; and Lee ilter 7x7

17 Summary and Conclusions (/). A mathematical approach or conversion o 4- to 3- Components. 2. % o negative values in Pv Multi-look 6x Multi-look 6x; and Lee ilter 7x7 Multi-look 2x2; and Lee ilter 7x7 Y4- Y4-R Y3-CU.2 (767/ ).65 (63259/ ) (73/ ) (223/ ) (4/ ) (9/ ) * multi-looking actors and iltering window size should be appropriate. 3. here is need to validate scattering decomposition scheme results or highly rugged terrain. -:validity o surace and volume scattering models??:-

18 [ ]= RU o [] (/) Scope 3-CSPD [(φ)]=cu o [ ] 3CSPD (5/7+θ+ɸ) Y3-RU-CU Range Y4-R Y4- PALSAR 2/4/8 Y3-RU-CU.

19 Pd Ps Pv May 6, 27 May 2, 27 Freeman-Durden Y3-CU Y4- Y4-R Y3-RU-CU