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Comparison of Noise Filtering Algorithms for SST

Comparison of Noise Filtering Algorithms for SST. 1. Conventional NLSST (no filtering noise) : SST CONV =a 1 T 11 +(T 11 -T 12 )*[a 2 *(T FG -273.15)+a 3 *sec θ ]+a 0 2. NLSST with smoothing of the atmospheric term (ATMS) : SST ATMS =a 1 T 11 +X*[a 2 *(T FG -273.15)+a 3 *sec θ ]+a 0

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Comparison of Noise Filtering Algorithms for SST

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  1. Comparison of Noise Filtering Algorithms for SST 1. Conventional NLSST (no filtering noise): SSTCONV=a1T11+(T11-T12)*[a2*(TFG-273.15)+a3*secθ]+a0 2. NLSST with smoothing of the atmospheric term (ATMS): SSTATMS=a1T11+X*[a2*(TFG-273.15)+a3*secθ]+a0 X=meanN×N(T11-T12), in this example N=7 3. NLSST with Marouan’s weighted BT smoothing (WBTS): SSTWBTS=a1Y11+(Y11-Y12)*[a2*(TFG-273.15)+a3*secθ]+a0 Yλ=meanN×N{[Tλ(ic,jc)-Tλ(i,j)]*exp[(Tλ(ic,jc)-Tλ(i,j))2/σ2]}/ /meanN×N{exp[(Tλ(ic,jc)-Tλ(i,j))2/σ2]} In this example σ2=0.01 • Tλ(ic,jc) is BT in the central pixel in the window • The pixels with larger difference Tλ(ic,jc)-Tλ(i,j) are accounted for with smaller weight • Therefore, WBTS cleans up mainly areas with uniform BT

  2. SSTconv-T0 T11-T12 • “Conventional” SST is noisy • BT difference T11-T12 is also noisy • No significant correlation between SSTconv and T11-T12

  3. SSTATMS-T0 X • Small-scale structure is revealed on atm. smoothed image of SSTATMS-T0 (left) • No this kind of structure in smoothed BT difference image (right) • No significant correlation between SSTconv and T11-T12

  4. T11-CRTM T12-CRTM • This regular structure is present in both BTS, at T11 and T12; it is cancelled out in T11 - T12 (right images on previous two slides)

  5. SSTCONV-SSTATMS T11-T12-X • The difference between SSTCONV - SSTATMS contains only random noise (left) • The same is the case for the difference between initial and smoothed atm. terms (right) • The atm. term smoothing DOES NOT introduce any regular structure in SST

  6. SSTCONV-T0 SSTBTS-T0 • The difference between SSTCONV and SSTATM contains only random noise (left) • The same is the case for the difference between initial and smoothed atm. terms (right) • The atm. term smoothing DOES NOT introduce any regular structure in SST

  7. SSTATMS-T0 SSTWBTS-T0 • The regular structure is more clear in SSTATMS (left) than in SSTWBTS (right) due to less intensive filtering by WBTS in non-uniform areas • Larger SST contrasts are noisier in SSTWBTS than in SSTATMS

  8. SSTCONV-SSTATMS SSTCONV-SSTWBTS • The difference SSTCONV-SSTWBTS contains random noise in relatively uniform SST areas • Non-uniform areas remain noisy • The difference SSTCONV – SSTATMS contains only uniform random noise

  9. SSTCONV-SSTATMS SSTCONV-SSTWBTS • The difference SSTCONV-SSTWBTS contains random noise in relatively uniform SST areas • Non-uniform areas remain noisy • The difference SSTCONV – SSTATMS contains only uniform random noise

  10. The difference between SSTWBTS and SSTATMS takes place mainly at high SST gradients, in the form of unfiltered random noise SSTWBTS-SSTATMS • Conclusions: • Smoothing of the atmospheric term uniformly filters out random noise from SST without introducing artifacts • Weighted BT smoothing filters noise only in relatively uniform areas, leaving SST gradient zone noisy; this is not good (e.g. for pattern recognition) • ATMS still seems to be the best way to reduce random noise in SST

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