forPresentingAtIGARSS2011vertical.pdf

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forPresentingAtIGARSS2011vertical.pdf

  1. 1. A TECHNIQUE FOR SPECTRAL PIXEL RECONSTRUCTION S. K. Patra, J. Saibaba, Geeta VaradanAdvanced Data Processing Research Institute (ADRIN) Dept. of Space, Hyderabad, India and S. K. Nayak Dept. of Electronics Berhampur University, Bhanja Vihar Orissa, India IGARSS 2011 Vancouver, Canada
  2. 2. OUTLINE OF THE WORK.. SPECTRAL RESPONSE (in mm)Band IKONOS QUICKBIRD IRS-P6 Centre FWHM Centre FWHM Centre FWHMBlu 0.485 0.07 0.485 0.07 Not AvailableGrn 0.56 0.08 0.56 0.08 0.555 0.07Red 0.66 0.06 0.66 0.06 0.650 0.06NIR 0.83 0.14 0.825 0.14 0.815 0.09 0.4-0.5mm 0.5-0.6 mm 0.6-0.7 mm 0.7-0.9 mm •NOT AVAILABLE IN IRS-P6! •HANDICAP FOR TRUE COLOR? •CREATE THE ONE.. S K Patra et.al.
  3. 3. SPECTRAL BANDS0.40 mm - 0.7 mm 0.87 mm – 1.5 mm~ visible ~ IR S K Patra et.al.
  4. 4. SPECTRAL-PIXELS FCC TRUE Color IKONOS RELATIVE SPECTRAL 1.20 RESPONSE 1.00 Relative Spectral Responsivity 0.80 0.60 0.40 0.20 0.00 400.00 500.00 600.00 700.00 800.00 900.00 1000.00 (0.20) Wavelength (nm) S K Patra et.al.
  5. 5. RADIOMETRIC REGISTRATIONTRUE COLOR FALSE COLOR Bt Gf Gt = T Rf Rt IRf Where , t = True Color f = False ColorB3  RED B4  REDB2  GRN B3  GRNB1  BLU B2  BLU Bt = aB + bB Gf + cB Rf + dB IRf Gt = aG+ bG Gf + cG Rf + dG IRf Rt = aR+ bR Gf + cR Rf + dR IRfwhere a, b, c and d are the elements ofmatrix T S K Patra et.al.
  6. 6. SPECTRAL BAND RECONSTRUCTION FCC TRUEB4  red B3  redB3  grn B2  grnB2  blu B1  blu NATURALB3  redNEWgrnB2  bluWhereNEW =¾ b2 + ¼ b4 ERDAS OUR METHOD IKONOS (b1:blue, b2:green,b3:red, b4:IR) S K Patra et.al.
  7. 7. OTHER SENSORS.. QUICKBIRDFCC TRUE OUR METHOD IRS-P6 LISS-3 LISS-4 AWiFS FCC NATURAL COLOR S K Patra et.al.
  8. 8. DECONVOLUTION and NOISE REDUCTIONWIENER FILTERING: [G (u, v)  H  (u, v)] F (u, v)  [ H (u, v)  H  (u, v)  Nu (u, v)]ITERATIVE EQUATION:qk 1 ( x, y )  qk ( x, y )  [ f ( x, y )  qk ( x, y )  h( x, y )]NOISE REDUCTION (BAYESIAN APPROACH): p( g | f ) p( f ) p( f | g )   p( g | f ) p( f ) S K Patra et.al.
  9. 9. DECONVOLUTION and NOISE REDUCTION WIENER PSF NIR •RESTORED •DENOISED FCC NATURAL •RECONSTRUCTED •RESTORED •DENOISEDLISS-4, IRS-P6 S K Patra et.al.
  10. 10. IMAGE QUALITY MEASURE NIR •DECONVOLVED •DECONVOLVED •DENOISED 60 80 Contrast Contrast 55 70 Deconvolv 50 ed and 60 Gray count denoised 50 45 origin Gray count al 40 40 deconvolv 30 35 ed 20 30 1050 1100 1150 1200 1140 1145 1150 1155 1160 Pixel No. Pixel No.LISS-4, IRS-P6 S K Patra et.al.
  11. 11. SPECTRAL PIXEL RECONSTRUCTION LISS-4, IRS-P6 IKONOSCOMPARABLE RESOLUTION OF 5.8M S K Patra et.al.
  12. 12. CONCLUSIONS• DEVELOPED A FRAMEWORK• TECHNIQUE CAN BE USED IN GENERATING ADDITIONAL INFORMATION• PROVIDES HIGH-QUALITY NATURAL COLOR IMAGES FOR A SENSOR NOT HAVING BLUE BAND S K Patra et.al.

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