Spaceborne Underwater Imaging 1 David J. Diner (JPL/CALTECH) John Martonchik (JPL/CALTECH) Yoav Y. Schechner (Technion, Israel) c Copyright All rights reserved.

2 Importance : Coastal Areas * Most human activity: safety, archaeology, recreation * Biological activity * Aerosol retrieval * Hydrosol retrieval Schechner, Diner, Martonchik NASA

bottom 3 Schechner, Diner, Martonchik

bottom l obj UW 4 Schechner, Diner, Martonchik

bottom 5 Schechner, Diner, Martonchik l obj UW 0 1 z exp z 

bottom 6 Schechner, Diner, Martonchik l obj UW 0 1 z exp z    atmos

bottom l obj UW 7 Schechner, Diner, Martonchik 0 1 z z exp  cos -1 exp   atmos cos -1

0 1 z z exp  cos z z exp  cos -1 z exp  cos -1 z exp  cos -1 t water = 8 Schechner, Diner, Martonchik

bottom l obj UW 9 Schechner, Diner, Martonchik

10 Schechner, Diner, Martonchik

z exp  cos -1 z exp  cos -1 t water = t = Schechner, Diner, Martonchik

12 z Sun beam water atmosphere bottom l obj UW t water = 1- i Schechner, Diner, Martonchik

13 z Sun beam water atmosphere a l sky bottom i Schechner, Diner, Martonchik

14 z Sun beam water atmosphere a b bottom l obj UW i l sky Schechner, Diner, Martonchik

15 Schechner, Diner, Martonchik l obj UW z depth map Simulation

16 Schechner, Diner, Martonchik Simulation simulated view z depth map

17 atmosphere a bottom i deep l sky Schechner, Diner, Martonchik

18 a i deep i t water = 1- a l obj UW l sky Schechner, Diner, Martonchik

19 i deep i l obj UW - t water = 1- a a l sky Schechner, Diner, Martonchik

20 l obj UW i deep i(x)i(x) - z Schechner, Diner, Martonchik z (x)z (x) l obj UW ( x ) -  cos e t surface e   atmos cos

Dependence on 21 l obj UW i deep i(x)i(x) - l obj UW (x)(x) z Schechner, Diner, Martonchik  atmos z( x )  Two unknowns per pixel x * Object radiance (descattered) * Depth map

Dependence on 22 i deep i(x)i(x) - l obj UW (x)(x)  atmos z(x)z(x)  Multispectral Remote Bathymetry No object descattering Infer depth map z(x) from spectral ratios Impressive Vary with unknown object, media Lyzenga’78, Philpot’89, Stumpf & Holderied’03

23 l obj UW i deep i(x)i(x) - l obj UW (x)(x) z Schechner, Diner, Martonchik  atmos z(x)z(x)  Dependence on is unknown

water atmosphere bottom 24 Schechner, Diner, Martonchik z (x)z (x) l obj UW ( x ) -  cos e e   atmos cos

orbit N F N F water atmosphere bottom 25 Schechner, Diner, Martonchik Lightfield Cam

Multi-angle Imaging SpectroRadiometer (MISR) Res: 275 m Bands: 446, 558, 672, 866 nm Polar orbit on NASA’s Terra Dec’

27 Schechner, Diner, Martonchik Simulation simulated view at nadir z depth map

28 Schechner, Diner, Martonchik Simulation simulated view z depth map

29 Schechner, Diner, Martonchik Simulation z depth map l obj N estimated

30 Schechner, Diner, Martonchik z z true depth estimated depth [meters]

31 log t surface [ i(x ) – i ] deep sounding cos z (x ) sounding  slope Schechner, Diner, Martonchik assume the same? (x ) sounding Unknown l obj UW

Sparse soundings z (x ) sounding Known assumed unpolarized (x ) sounding Unknown l obj UW 32

T surface t atmosphere 33 deep i(x) – i = l obj UW ( x ) - z (x)z (x) cos e  u q T surface u q - - pol independent of x Schechner, Diner, Martonchik

8 Spectral bands, three of which are polarimetric Multiangle SpectroPolarimetric Imager (MSPI) Airborne camera (AirMSPI) In nose of NASA ER-2 high-altitude aircraft 34

35 Spaceborne Underwater Imaging Yoav Schechner, David Diner, John Martonchik