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Optics Express

Optics Express

  • Editor: Michael Duncan
  • Vol. 13, Iss. 11 — May. 30, 2005
  • pp: 4250–4262
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Upwelling radiance distribution camera system, NURADS

Kenneth J. Voss and Albert L. Chapin  »View Author Affiliations


Optics Express, Vol. 13, Issue 11, pp. 4250-4262 (2005)
http://dx.doi.org/10.1364/OPEX.13.004250


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Abstract

We have built a new fisheye camera radiometer to measure the in-water spectral upwelling radiance distribution. This instrument measures the radiance distribution at six wavelengths and obtains a complete suite of measurements (6 spectral data images with associated dark images) in approximately 2 minutes (in clear water). This instrument is much smaller than previous instruments (0.3 m in diameter and 0.3 m long), decreasing the instrument self-shading. It also has improved performance resulting from enhanced sensor sensitivity and a more subtle lens rolloff effect. We describe the instrument, its characterization, and show data examples from both clear and turbid water.

© 2005 Optical Society of America

1. Introduction

The radiance distribution is described by the collection of radiance data in all directions coming to a single point. Measurement of the upwelling radiance distribution in the ocean is difficult because of the number of observations required, the variability of the light field due to surface waves, and instrument self-shading, yet the upwelling radiance distribution is vitally important in ocean remote sensing. Ocean remote sensing algorithms have typically treated the ocean as a lambertian surface (radiance independent of viewing geometry). However, because the ocean reflectance varies with view geometry and illumination conditions, knowledge of the upwelling radiance distribution is required for accurate retrieval of oceanic parameters.[1

1. A. Morel and B. Gentili, “Diffuse reflectance of oceanic waters. III. Implication of bidirectionality for the remote-sensing problem,” Appl. Opt. 35, 4850–4862 (1996). [CrossRef] [PubMed]

]

More recently a series of instruments have been built, for use in the water, based on this fisheye technique, but using electro-optic cameras and remotely controlled spectral filter changers. The first of these [6

6. K. J. Voss, “Electro-optic camera system for measurement of the underwater radiance distribution,” Opt. Eng. 28, 241–247 (1989).

] included charge injection device (CID) electro-optic camera systems for both the upwelling and downwelling radiance distribution. This system consisted of three cans of instruments, with upwelling and downwelling systems in separate cans, along with a third can for the control electronics. The filter changer allowed selection of one of 4 spectral filters (25.4 mm interference filters), along with neutral density filters to adjust the overall sensitivity. These cameras were digitized with 8-bit frame grabbers, and did not have an intrinsically high dynamic range. However, by coating the dome/window of the downwelling camera for zenith angles less than 45 degrees, and taking into account the lens system rolloff characteristics, the dynamic range of the downwelling and upwelling radiance distribution could be accommodated. One useful characteristic of the CID architecture was that excess light in one pixel does not spread into neighboring pixels (bloom).

Because of the interest in the surface upwelling radiance we found that we were only using the upwelling data from the system. To get accurate radiance distributions, without the effect of ship shadow, required floating the instrument away from the ship, which made it impossible to take upwelling/downwelling profiles or collect useful downwelling information. The size of the instrument, including the buoy to float it, caused a noticeable shadow effect in the images even in clear water [10

10. J. P. Doyle and K. J. Voss, “3D Instrument Self-Shading effects on in-water multi-directional radiance measurements,” presented at Ocean Optics XV, Monaco, 16–20 Oct. 2000.

]. This effect had been seen with the earlier instrument [11

11. W. S. Helliwell, G. N. Sullivan, B. Macdonald, and K. J. Voss, “A finite-difference discrete-ordinate solution to the three dimensional radiative transfer equation,” Transport Theory and Statistical Physics 19, 333–356 (1990). [CrossRef]

] and was smaller than before, however it was still a noticeable perturbation.

Because of instrument self-shading issues, and the desire to collect only upwelling radiance distribution data, the NURADS instrument was developed. The system also has a filter changer, embedded computer and hard drive, CCD camera, and compass/tilt/roll sensor. However with advances in technology, this whole instrument package is only 0.3 m in diameter and 0.3 m long and also requires less floatation. The reduced self-shading and several other improvements have helped the instrument acquire more accurate radiance distribution data. This paper will describe this instrument, and provide some sample data from the instrument.

2. Fundamental NURADS instrument description

The instrument is based on an Apogee CCD array camera system (AP 260Ep) that uses the KAF-2610E CCD array. The camera housing includes the frame grabber electronics and interfaces directly with the embedded computer (Versalogic Panther, EPM-CPU-6) via a standard parallel interface. The frame grabber digitizes the images at 16 bit resolution, the final system dynamic range will be discussed below. Included in the instrument is a 20 Gbyte 2.5” hard drive on which the camera images and auxiliary data is stored. There is an embedded EZ-Compass-3 (Advanced Orientation Systems, Inc.) that collects the tilt/roll/compass information and transfers it to the computer over a serial interface. This information is logged to the hard drive continuously in the background during camera operation using the Windmill program (Windmill Software, Ltd.). The system uses a fisheye adapter lens, designed for a Nikon Coolpix 950 camera (FC-E8), a custom lens relay system, and a filter changer (MFW, Homeyer) (also controlled over a serial interface) to form the fisheye camera image and provide spectral filtering. The filter changer uses 25.4 mm interference filters, and allows the selection of one of 6 spectral filters for the image. The embedded computer is controlled by a surface laptop computer by use of the Timbuktu (Netopia) remote control software over an Ethernet link. While the data is stored on the embedded computer hard drive, once data collection is completed the data on the hard drive can be extracted via an ftp (file transfer protocol) transfer.

Because of speed advances in the camera frame grabbing technology, enhanced sensitivity of the CCD array, and faster optics, in clear water a complete set of data (6 light images, 6 dark images, one with each spectral filter) can be obtained in 2 minutes. The embedded computer controls the camera with a combination of MaxIM DL (Diffraction Limited), Microsoft Excel, and Microsoft Basic programs. In typical operation, the camera is run continually during the data collection period. By taking multiple data sets, data can be excluded where the camera tilt/roll exceeds some threshold (usually 5 degrees), clouds are determined to be causing a problem with the incident light field, or some other temporary artifact is in the image. Multiple images are also averaged to reduce the effect of bright light rays due to waves at the air-sea interface. In 30 minutes, 15 complete sets of data (approximately 90 Mbytes of data) can be acquired.

3. Characterization and calibration

The method to characterize and calibrate the fish eye systems has been described earlier [12

12. K. J. Voss and G. Zibordi, “Radiometric and geometric calibration of a spectral electro-optic “fisheye’camera radiance distribution system,” J. Atmosph. and Ocean. Techn. 6, 652–662 (1989). [CrossRef]

]. We will concentrate on the specific results for this system.

The basic characteristics of the system relevant to the radiance distribution measurements are the lens system rolloff function, camera linearity, camera noise characteristics (dark noise and readout noise), polarization sensitivity, and spectral calibration of filters/system. We will start with camera noise characteristics.

Fig. 1. Picture of NuRADS system (fore ground) with the older RADS-II system (background). The new system is significantly more compact than the older system.

3.1 Camera noise characteristics

To see the background readout noise, and an indication of the dark noise level of the camera system, we averaged dark images (shutter closed) at several different integration times. The images were averaged, pixel-by-pixel to see if the variation was correlated with individual pixels, or was uniform across the array. Figure 3 shows a histogram of this pixel average (left) and the histogram for the standard deviation of the individual pixel averages (right). The Fig. below shows that the spread in integration times is very small for less than 2 sec, at 5 sec there is more variation. In terms of the standard deviation of the individual pixel averages, the average spread does not change significantly even at 5 sec integration. These two graphs imply that at longer integration times, there is some pixel-to-pixel variation in dark counts, but the noise does not increase. Thus subtracting a dark image from the data image is a better strategy then subtracting one overall average number. In our data collection we take a dark image for each data image, and subtract (pixel-by-pixel) this image from the data image. These graphs also show that the intrinsic noise in the system is on the order of 4 counts, thus the system is easily operated as a 14 bit system and pixel averaging can increase the effective dynamic range of the system.

Fig. 3. Dark noise data for the instrument. Left Fig. shows that the average pixel count of the dark/readout noise is approximately 2675 counts, and only increases when the integration time is greater than 2 seconds. Right Fig. shows that the standard deviation in the individual pixel averages is on the order of 4 counts.

3.2 Camera linearity

The CCD camera is inherently a very linear device, and this system was no exception. This test will not be discussed in detail here, but it is similar to the results seen in the earlier system [5

5. R. C. Smith, R. W. Austin, and J. E. Tyler, “An oceanographic radiance distribution camera system,” Appl. Opt. 9, 2015–2022 (1970). [CrossRef] [PubMed]

], with the camera system displaying linearity (within 3%) over 3 orders of magnitude of incident flux.

3.3 Angular calibration

The natural projection of an ideal fisheye lens is a simple linear equation:

θ=Kr
(1)

where θ (in degrees) is the angle from nadir, r is the radial distance, in pixels, from the center of the image, and K (in degrees/pixel) is a calibration constant found through calibration.

We use a hemispherical dome as the window in the instrument. If the system is constructed, and adjusted properly, the first principal plane of the optical system will be at the center of curvature of the hemispherical dome. At this position, rays which make it through the lens system will enter the dome perpendicular to the local dome surface, thus there will be little refraction, and the angular mapping of pixel location to a given radiance direction is straightforward. To check whether this is done properly we determine the calibration constant K in both air and water. If they are the same, then the instrument is set up properly. Before and after each deployment we do the angular calibration to help determine if any changes have happened in the optics. A typical example is shown below in Fig. 4, for an in-water calibration. The K derived from this graph was 0.469±0.004. The r2 for this regression was 0.9995.

A time series of angular calibrations for a NuRADS instruments is shown in Fig. 5. In this graph the in-water calibrations are shown as open circles, while the in-air calibrations are shown as filled circles. As can be seen, the angular calibration is both very stable, and the differences between the air and water values are small. In some later calibrations, only air or water calibrations were performed to verify instrument stability. The small variations around a constant value are partially real (due to small adjustments of instrument focus or the result of taking apart the lens system and putting it back together) and partially a small error in the calibration results. The small source used in the calibration, when imaged, takes up more than one pixel in the image, so there are errors in determining the true center pixel of the source image.

Note that because of the fisheye projection, the solid angle represented by each pixel varies, depending on nadir angle. Since θ(in radians) is θ=K(π/180) r, then dθ=K(π/180) dr.

The pixel area (dA) is given by dA=rdϕ dr, and solid angle is defined by dΩ=sin θ dθ dϕ. Thus represented by each pixel (dA) is:

dΩ=K(π180)sin(θ)rdA.
(2)

At a nadir angle of 10 degrees, each pixel represents 7×10-5 sr, while at 70 degrees each pixel represents 5×10-5 sr.

Fig. 4. An example angular calibration. A small source is imaged by the camera, and a series of images is obtained as the camera is rotated. For each image, the source location in the image is determined and correlated with the rotation angle. The line is a linear least squares fit to the data.
Fig. 5. Angular calibration history for one of the NuRADS camera systems. In this graph the open circles represent K for in-water calibrations while the filled circles represent K for in-air calibrations. The error bars represent the error in determining K from the calibration data.

3.4 Immersion calibration

The immersion calibration determines the difference in camera system response between measurements made in-air (where most of the calibrations are done) versus those in-water (where the desired measurements are). For radiometers with flat windows this is caused by the difference between air-glass and water-glass transmission and the index of refraction (n2) effect between air (inside the instrument) and water (outside). With the fisheye system, and the hemispherical dome window, there is another effect that offsets this n2 refraction effect. In essence the apparent aperture size of the system varies whether it is in-water or in-air. Hence, we must do a calibration to determine the immersion factor. The calibration is done in the following manner. The instrument is placed, dry, in a barrel and a reflectance plaque is suspended above this barrel at 45 degrees to the vertical. The plaque is illuminated by a 1000W FEL lamp. Images of the plaque are obtained as the water level in the tank is raised above the level of the dome window. Several measurements are made with different water levels, with the window submerged, to determine the water attenuation. The average of a 20×20 pixel area, centered on the plaque, is obtained at each measurement point. The attenuation coefficient of the water is determined from the measurements at the different water levels, and is used to correct for attenuation effects. The apparent radiance that the plaque should have at the front of the camera window is Lwater and Lair, when in water and air respectively. This can be calculated by compensating for the air-water interface effects, and water attenuation as:

Lwater=Lairecrn2Twaterair.
(3)

Where e-cr is the attenuation from the surface of the water to the front of the dome window, n is the index of refraction of water, and Twater-air is the Fresnel transmission through the air-water interface.) Lwater and Lair, along with the pixel averages when the window was dry (#air) vs. wet (#water) are used to determine the immersion correction, M.

M=Lwater#air(#waterLair)
(4)

Typical immersion factors are on the order of 1.85.

3.5 Camera lens rolloff

Fig. 6. Rolloff functions for NuRADS (blue crosses) and for RADS-II (red crosses). As can be seen, the rolloff for the NuRADS system is much less severe than for the RADS-II system. At 80°, the rolloff is only 0.9 versus 0.2 for the older system.

The increase in this rolloff factor increases the measurement accuracy at large angles because the inverse of this number is used to correct the radiance images. Thus noise and other errors are only multiplied by a factor of 1.1 at 80° in the new system, rather than 5 as in the old system.

3.6 Spectral calibration

The spectral calibration was performed by measuring the filter transmission of each filter in a spectro-photometer. Since the filters are only nominally 10 nm wide, there are no other sharp features in the system that would significantly effect the calibration. Any well blocked, 2.54 cm interference filter can be used; the characteristics of the filters we chose are shown in Table 1. In addition to the blocking built into these filters, additional blocking was

Table 1. Spectral characteristics of the current NuRADS configuration.

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provided to reduce the infrared response (Schott glass BG18), and Wratten filters for some of the red bands to provide extra blocking for the blue light. Since this instrument is designed to measure upwelling light at the surface, the blocking requirements for the blue light is less severe than a profiling instrument. After constructing the system, with the filter combinations to be used, tests are also performed in the laboratory (imaging an FEL illuminated reflectance plaque) and in full sunlight (imaging a sunlight illuminated reflectance plaque). In these tests, additional filters are placed between the camera and the plaque which either block the passband of the filter, or some other spectral region. Measurements taken in this way can determine the residual out of band response. In these tests, our filter combinations were sufficiently blocked to keep total integrated out of band response to less than 1% for both lamp and solar illuminated targets.

3.7 Polarization Sensitivity

The upwelling radiance distribution in the ocean is partially polarized, thus to make accurate measurements of the total radiance (unpolarized) it is important that the instrument be insensitive to the incident polarization. Measurements of the camera optical system have shown that the polarization sensitivity of the optical system is less than 1%. Our system window is a plastic dome, and while these may show stress bi-refringence [13

13. F. L. Pedrotti and L. S. Pedrotti, Introduction to Optics (Prentice Hall, New Jersey, 1993).

] through photoelasticity, as long as the optical system behind the window is polarization insensitive, this will have no effect on the final measurement. We also enter the window at very close to normal incidence, hence Fresnel transmittance has no polarization effect. Thus our polarization sensitivity is less than 1%.

3.8 Absolute calibration

Finally an absolute calibration is performed. We are currently using a radiance source made of a reflecting plaque (99% spectralon plaque) and a 1000W FEL lamp. The history of calibration for one of the instruments is shown in Fig. 7. Note in this Fig., Filter 5 has almost exactly the same numerical values as Filter 4, thus the symbol is hidden. With these calibration coefficients, and an integration time of 1 sec, each count represents on the order of 30 pW cm-2 nm-1 sr-1. Full scale at 1 sec integration time is then 2 µW cm-2 nm-1 sr-1.

Fig. 7. Calibration history of one of the NuRADS camera systems. As can be seen the absolute calibration is fairly stable over the instruments history.

4. Sample data

4.1 clear water case

The data shown below was acquired on 10/22/2003 off of Honolulu, Hawaii. The solar zenith angle during these measurements was 38° (refracted in-water angle would be 27°). An image is shown for each wavelength. The water was very clear, the Chlorophyll concentration (Chl) was approximately 0.1 mg/m3.

In these clear water images several things are evident. The first feature is that the minimum in the radiance distribution is actually on the sun side of the nadir, not on the anti-solar side. While it is not as obvious in these false color images as it is in the grey scale images, the anti-solar point is evident as the point where the bright, refracted rays converge. The anti-solar point is also evident in the longer wavelength (red) images, as the place where the instrument self shadow is evident. Since the instrument is a cylinder, with the measurement window in the center of the bottom of the cylinder, the shadow actually extends towards the surface from the anti-solar point. In all the shorter wavelength images, even though the instrument is approximately 30 m or more from the ship, the ship hull is evident on the horizon. It is difficult to quantify the ship shadows magnitude, but (given that the ship was only 15m long) it probably has less than a 1% effect on the upwelling irradiance field.[14

14. J. Piskozub, “Effect of ship shadow on in-water irradiance measurements,” Oceanologia 46, 103–112 (2004).

] Finally, while the radiance distribution is not isotropic, the range of values from nadir to the horizon is limited to a factor of 3 or less.

These images are individual “snapshots” of the instantaneous upwelling radiance distribution, as such there are various other artifacts in the image. Some of these are evident as the line in the upper right of 412 nm (instrument cable), or some of the other bright spots on the right of the image that are harder to identify. At times we have seen fish in the images. In general we use averages of images when applying the data, in which case the individual artifacts are either masked out or disappear through averaging.

Fig. 8. Upwelling radiance distribution images in clear water. Solar zenith angle is 38 degrees in air. Nadir angles are linearly related to the radius from the center. The center of each image is the nadir, the edge of the circle is the horizon (90 deg nadir angle). At very large nadir angles, in the lower wavelengths, the ship shadow or hull is evident and is labeled in one of the graphs At the reddest wavelength the direct instrument self-shadow is quite evident and is labeled in the graph.

Two convenient simplifications, describing the shape of the upwelling radiance distribution, are the average cosine of the upwelling radiance distribution (µu) and Qu:

μu=EuEOu
(5)
Qu=EuLu.
(6)

Where Eu is the upwelling irradiance, Eou is the upwelling scalar irradiance, and Lu is the nadir upwelling radiance. For an isotropic radiance distribution, Qu would be equal to π and µu would be equal to 0.5. Table 2 shows Qu and µu calculated from the images shown. As can be seen Qu is slightly higher than π, as reflected in the images by the brightening in radiance towards the horizon. µu is slightly less than 0.5. The variation in these factors reflects the variation in the pure water absorption, with Qu increasing towards the longer, red, more absorbed wavelengths. The last column is the Qu predicted by the model of Morel et al.[15

15. A. Morel, D. Antoine, and B. Gentili, “Bidirectional reflectance of oceanic waters: accounting for Raman emission and varying particle scattering phase function,” Appl. Opt. 41, 6289–6306 (2002). [CrossRef] [PubMed]

]. Our measured Qu is somewhat smaller than the model prediction, except at 616 nm. At 616 nm, instrument self-shadow is obvious in the measurement and may be decreasing Lu more than Eu. In all cases though the two values are within 10% of each other.

Table 2. Qu, µu, and Lu for the clear water radiance distributions. The last column [Qu(MAG)] is Qu predicted by Morel et al.[15].

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Also note that Lu decreases from the blue to the red reflecting the obvious blue color of the water.

4.2 Turbid water case

In these turbid case 2 waters, the radiance distribution has a lot more variation from nadir to the horizon. This is reflected in the Qu and µu factors shown in Table 3. The spectral variation of the parameters, and the underlying radiance distribution, reflects the influence of dissolved organic material in these turbid waters, case 2 waters. In particular, the increased absorption at the lower wavelengths causes Qu to be higher, and µu to be lower than in the clear water case. As the wavelength increases, total absorption decreases, and Qu decreases.

Table 3. Qu, µu, and Lu for the turbid water radiance distributions.

table-icon
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This continues until 616 nm, where the water absorption becomes significant and once again Qu increases. It can be seen that, as expected in this turbid coastal water, the maximum upwelling nadir radiance is in the green, with little light coming out at the blue wavelengths.

Fig. 9. Upwelling radiance distribution images in turbid, coastal water. Solar zenith angle is 33 degrees in air. Figure geometry is the same as Fig. 8.

Also note the significant amount of nadir radiance at the red wavelength. These Qu’s are within the range shown in [16

16. G. Zibordi and J.-F. Berthon, “Relationships between the Q-factor and seawater optical properties in a coastal region,” Limnol. Oceanogr. 46, 1130–1140 (2001). [CrossRef]

]. However, the model suggested in [16

16. G. Zibordi and J.-F. Berthon, “Relationships between the Q-factor and seawater optical properties in a coastal region,” Limnol. Oceanogr. 46, 1130–1140 (2001). [CrossRef]

] does not extend to these turbid waters, and there is not a good model with which to compare. In fact, this is one of the research areas for which this instrument will be used.

5. Conclusion

This instrument represents a significant advance in the measurement of the upwelling radiance distribution. The instrument has already been used during several cruises in Hawaii (clear water), the Cheasapeake Bay (turbid coastal water). There are two immediate areas in which data from this instrument will be applied. The first is to improve, or validate, BRDF models for remote sensing. As stated earlier, for remote sensing, the ocean is commonly assumed to be a lambertian surface (radiance independent of viewing geometry). This radiance distribution data can be used to empirically derive the correct variation of the satellite viewed radiance with viewing angle and to test existing and future models. These models are also used to predict Qu, and we are working on a model of Qu in turbid water. In addition, since the radiance distribution is fundamentally dependent on the backscattering phase function of the water, this data can be used to test models of the in-water light field and constrain this phase function.

Acknowledgments

This work was supported by NASA (NNG04HZ21C). We also thank Dennis Clark (NOAA/NESDIS) for his support in building these instruments. ONR (N000149910008) has also been supported our development of radiance distribution instruments.

References and Links

1.

A. Morel and B. Gentili, “Diffuse reflectance of oceanic waters. III. Implication of bidirectionality for the remote-sensing problem,” Appl. Opt. 35, 4850–4862 (1996). [CrossRef] [PubMed]

2.

J. E. Tyler, “Radiance distribution as a function of depth in an underwater environment,” Bull. Scripps Inst. Oceanogr. 7, 363–41 (1960).

3.

E. Aas and N. K. Hojerslev, “Analysis of underwater radiance distribution observations: apparent optical properties and analytical functions describing the angular radiance distributions,” J. Geophys. Res. 104, 8015–8024 (1999). [CrossRef]

4.

K. Miyamoto, “Fish Eye Lens,” J. Opt. Soc. Am. 54, 1060–1061 (1964). [CrossRef]

5.

R. C. Smith, R. W. Austin, and J. E. Tyler, “An oceanographic radiance distribution camera system,” Appl. Opt. 9, 2015–2022 (1970). [CrossRef] [PubMed]

6.

K. J. Voss, “Electro-optic camera system for measurement of the underwater radiance distribution,” Opt. Eng. 28, 241–247 (1989).

7.

K. J. Voss and A. L. Chapin , “Next generation in-water radiance distribution camera system,” in Ocean Optics XI, G. D. Gilbert, eds., Proc. SPIE1750, 384–387 (1992).

8.

K. J. Voss, C. D. Mobley, L. K. Sundman, J. Ivey, and C. Mazell, “The spectral upwelling radiance distribution in optically shallow waters,” Limnol. Oceanogr. 48, 364–373 (2003). [CrossRef]

9.

K. J. Voss and A. Morel, “Bidirectional reflectance function for oceanic waters with varying chlorophyll concentrations: measurements versus predictions,” Limnol. Oceanogr. 50, 698–705 (2005). [CrossRef]

10.

J. P. Doyle and K. J. Voss, “3D Instrument Self-Shading effects on in-water multi-directional radiance measurements,” presented at Ocean Optics XV, Monaco, 16–20 Oct. 2000.

11.

W. S. Helliwell, G. N. Sullivan, B. Macdonald, and K. J. Voss, “A finite-difference discrete-ordinate solution to the three dimensional radiative transfer equation,” Transport Theory and Statistical Physics 19, 333–356 (1990). [CrossRef]

12.

K. J. Voss and G. Zibordi, “Radiometric and geometric calibration of a spectral electro-optic “fisheye’camera radiance distribution system,” J. Atmosph. and Ocean. Techn. 6, 652–662 (1989). [CrossRef]

13.

F. L. Pedrotti and L. S. Pedrotti, Introduction to Optics (Prentice Hall, New Jersey, 1993).

14.

J. Piskozub, “Effect of ship shadow on in-water irradiance measurements,” Oceanologia 46, 103–112 (2004).

15.

A. Morel, D. Antoine, and B. Gentili, “Bidirectional reflectance of oceanic waters: accounting for Raman emission and varying particle scattering phase function,” Appl. Opt. 41, 6289–6306 (2002). [CrossRef] [PubMed]

16.

G. Zibordi and J.-F. Berthon, “Relationships between the Q-factor and seawater optical properties in a coastal region,” Limnol. Oceanogr. 46, 1130–1140 (2001). [CrossRef]

OCIS Codes
(010.4450) Atmospheric and oceanic optics : Oceanic optics
(120.5630) Instrumentation, measurement, and metrology : Radiometry

ToC Category:
Research Papers

History
Original Manuscript: May 3, 2005
Revised Manuscript: May 17, 2005
Published: May 30, 2005

Citation
Kenneth Voss and Albert Chapin, "Upwelling radiance distribution camera system, NURADS," Opt. Express 13, 4250-4262 (2005)
http://www.opticsinfobase.org/oe/abstract.cfm?URI=oe-13-11-4250


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References

  1. A. Morel and B. Gentili, �??Diffuse reflectance of oceanic waters. III. Implication of bidirectionality for the remote-sensing problem,�?? Appl. Opt. 35, 4850-4862 (1996). [CrossRef] [PubMed]
  2. J. E. Tyler, �??Radiance distribution as a function of depth in an underwater environment,�?? Bull. Scripps Inst. Oceanogr. 7, 363-41 (1960).
  3. E. Aas and N. K. Hojerslev, �??Analysis of underwater radiance distribution observations: apparent optical properties and analytical functions describing the angular radiance distributions,�?? J. Geophys. Res. 104, 8015 �?? 8024 (1999). [CrossRef]
  4. K. Miyamoto, �??Fish Eye Lens,�?? J. Opt. Soc. Am. 54, 1060- 1061 (1964) [CrossRef]
  5. R. C. Smith, R. W. Austin and J. E. Tyler, �??An oceanographic radiance distribution camera system,�?? Appl. Opt. 9, 2015-2022 (1970). [CrossRef] [PubMed]
  6. K. J. Voss, �??Electro-optic camera system for measurement of the underwater radiance distribution,�?? Opt. Eng. 28, 241-247 (1989).
  7. K. J. Voss and A. L. Chapin, �??Next generation in-water radiance distribution camera system,�?? in Ocean Optics XI, G. D. Gilbert, eds., Proc. SPIE 1750, 384 �?? 387 (1992).
  8. K. J. Voss, C. D. Mobley, L. K. Sundman, J. Ivey, and C. Mazell, �??The spectral upwelling radiance distribution in optically shallow waters,�?? Limnol. Oceanogr. 48, 364 �?? 373 (2003). [CrossRef]
  9. K. J. Voss and A. Morel, �??Bidirectional reflectance function for oceanic waters with varying chlorophyll concentrations: measurements versus predictions,�?? Limnol. Oceanogr. 50, 698 �?? 705 (2005). [CrossRef]
  10. J. P. Doyle and K. J. Voss, �??3D Instrument Self-Shading effects on in-water multi-directional radiance measurements,�?? presented at Ocean Optics XV, Monaco, 16-20 Oct. 2000.
  11. W. S. Helliwell, G. N. Sullivan, B. Macdonald, and K. J. Voss, �??A finite-difference discrete-ordinate solution to the three dimensional radiative transfer equation,�?? Transport Theory and Statistical Physics 19, 333-356 (1990). [CrossRef]
  12. K. J. Voss and G. Zibordi, �??Radiometric and geometric calibration of a spectral electro-optic "fisheye' camera radiance distribution system,�?? J. Atmosph. and Ocean. Techn. 6, 652-662 (1989). [CrossRef]
  13. F. L. Pedrotti and L. S. Pedrotti, Introduction to Optics (Prentice Hall, New Jersey, 1993).
  14. J. Piskozub, �??Effect of ship shadow on in-water irradiance measurements,�?? Oceanologia 46, 103-112 (2004).
  15. A. Morel, D. Antoine, and B. Gentili, �??Bidirectional reflectance of oceanic waters: accounting for Raman emission and varying particle scattering phase function,�?? Appl. Opt. 41, 6289 �?? 6306 (2002). [CrossRef] [PubMed]
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