Noise-equivalent Change Research Articles

Evaluation of Radiometric Performance for the Thermal Infrared Sensor Onboard Landsat 8

The radiometric performance of remotely-sensed images is important for the applications of such data in monitoring land surface, ocean and atmospheric status. One requirement placed on the Thermal Infrared Sensor (TIRS) onboard Landsat 8 was that the noise-equivalent change in temperature (NEΔT) should be ≤0.4 K at 300 K for its two thermal infrared bands. In order to optimize the use of TIRS data, this study investigated the on-orbit NEΔT of the TIRS two bands from a scene-based method using clear-sky images over uniform ground surfaces, including lake, deep ocean, snow, desert and Gobi, as well as dense vegetation. Results showed that the NEΔTs of the two bands were 0.051 and 0.06 K at 300 K, which exceeded the design specification by an order of magnitude. The effect of NEΔT on the land surface temperature (LST) retrieval using a split window algorithm was discussed, and the estimated NEΔT could contribute only 3.5% to the final LST error in theory, whereas the required NEΔT could contribute up to 26.4%. Low NEΔT could improve the application of TIRS images. However, efforts are needed in the future to remove the effects of unwanted stray light that appears in the current TIRS images.

On-Orbit Radiometric Performance of the Landsat 8 Thermal Infrared Sensor

The Thermal Infrared Sensor (TIRS) requirements for noise, stability, and uniformity were designed to ensure the radiometric integrity of the data products. Since the launch of Landsat 8 in February 2013, many of these evaluations have been based on routine measurements of the onboard calibration sources, which include a variable-temperature blackbody and a deep space view port. The noise equivalent change in temperature (NEdT) of TIRS data is approximately 0.05 K @ 300 K in both bands, exceeding requirements by about a factor of 8 and Landsat 7 ETM+ performance by a factor of 3. Coherent noise is not readily apparent in TIRS data. No apparent change in the detector linearization has been observed. The radiometric stability of the TIRS instrument over the period between radiometric calibrations (about 40 min) is less than one count of dark current and the variation in terms of radiance is less than 0.015 \(W/m^2/sr/\mu m\) (or 0.13 K) at 300 K, easily meeting the short term stability requirements. Long term stability analysis has indicated a degradation of about 0.2% or less per year. The operational calibration is only updated using the biases taken every orbit, due to the fundamental stability of the instrument. By combining the data from two active detector rows per band, 100% detector operability is maintained for the instrument. No trends in the noise, operability, or short term radiometric stability are apparent over the mission life. The uniformity performance is more difficult to evaluate as scene-varying banding artifacts have been observed in Earth imagery. Analyses have shown that stray light is affecting the recorded signal from the Earth and inducing the banding depending on the content of the surrounding Earth surface. As the stray light effects are stronger in the longer wavelength TIRS band11 (12.0 \(\mu m\)), the uniformity is better in the shorter wavelength band10 (10.9 \(\mu m\)). Both bands have exceptional noise and stability performance and band10 has generally adequate uniformity performance and should currently be used in preference to band11. The product uniformity will improve with the stray light corrections being developed.

Comparison of Long-Wave Infrared Quantum-Dots-in-a-Well and Quantum-Well Focal Plane Arrays

This paper reports on a comparison between a commercially available quantum-well infrared focal plane array (FPA) and a custom quantum-dot (QD)-in-a-well (DWELL) infrared FPA in the long-wave infrared (LWIR). The DWELL detectors consist of an active region composed of InAs QDs embedded in In0.15Ga0.85As quantum wells. DWELL samples were grown using molecular beam epitaxy and fabricated into 320 times 256 pixels FPA with a flip-chip indium bump technique. Both the DWELL and QmagiQ commercial quantum-well detector were hybridized to an Indigo ISC9705 readout circuit and tested in the same camera system. Calibrated blackbody measurements at a device temperature of 60 K with LWIR optics yield a noise equivalent change in temperature of 17 mK and 91 mK for quantum-well and DWELL FPAs operating at 0.95- and 0.58-V biases, respectively. The comparison of the DWELL and quantum-well FPA when imaging a 35degC black body showed that the DWELL had a signal-to-noise ratio of 124 while the quantum-well FPA showed 1961. As well, the quantum-well FPA showed a higher collection efficiency of 1.3 compared to the DWELL.

Noise-equivalent change in radiance for misalignment noise in a double-sided interferogram: erratum

In a previous publication [Appl. Opt.42, 6292 (2003)], information on page 6296 was presented inaccurately. These inaccuracies are corrected here.

Noise-equivalent change in radiance for misalignment noise in a double-sided interferogram

Engineers designing optical alignment servo systems for Michelson interferometers and Fourier-transform infrared spectrometers need to predict the amount of noise expected from the small and randomly varying amounts of misalignment that occur as the servo attempts to maintain alignment while taking data. A formula is derived for the noise-equivalent change in radiance due to this effect and the formula's accuracy is demonstrated by comparison of its predictions to the errors found in simulated interferometer measurements contaminated by misalignment noise.

Noise-equivalent change in radiance for sampling noise in a double-sided interferogram.

The formula for the noise-equivalent change in radiance (NEdN) for sampling noise [Appl. Opt. 38, 139 (1999)] can work well when applied to the double-sided interferograms of radiance spectra dominated by isolated emission lines, but it does not work well when applied to broad, slowly varying radiance spectra such as a Planck blackbody curve. The modified formula for the sampling-noise NEdN works well when applied to the double-sided interferograms of both types of radiance spectra.

Comparison of SNR image quality metrics for remote sensing systems

Different definitions of the signal-to-noise ratio (SNR) are be- ing used as metrics to describe the image quality of remote sensing systems. It is usually not clear which SNR definition is being used and what the image quality of the system is when an SNR value is quoted. This paper looks at several SNR metrics used in the remote sensing community. Image simulations of the Kodak Space Remote Sensing Camera, Model 1000, were produced at different signal levels to give insight into the image quality that corresponds with the different SNR metric values. The change in image quality of each simulation at different signal levels is also quantified using the National Imagery Interpretability Rating Scale (NIIRS) and related to the SNR metrics to better under- stand the relationship between the metric and image interpretability. An analysis shows that the loss in image interpretability, measured as DNI- IRS, can be modeled as a linear relationship with the noise-equivalent change in reflection (NE Dr). This relationship is used to predict the val- ues that the various SNR metrics must exceed to prevent a loss in the interpretability of the image from the noise. © 2001 Society of Photo-Optical