Radiometric Calibration Algorithms Research Articles

Radiometric calibration and measurement algorithm for electrical inspection solar-blind ultraviolet cameras

Radiometric calibration and measurement algorithm for electrical inspection solar-blind ultraviolet cameras

Radiometric calibration algorithm for high dynamic range infrared imaging system

The infrared imaging system with high dynamic range is one of the most prime candidates in the area of quantitative infrared radiometry and thermometry applications. As the foundation of the measurement processes, radiometric calibration is the inception procedure which will be studied emphatically in this paper. Conventional radiometric calibration algorithm is not suitable for high dynamic range infrared imaging systems that requires the flexibility of adjusting the integration time and transmittance according to characteristics of the detected target. Unfortunately, fixed calibration coefficients will inevitably arouse the deterioration of the calibration accuracy in the case of variable integration time or the transmittance. For the purpose of solving above issues, effects of integration time and transmittance on calibration are analyzed in detail. A modified calibration algorithm considering the integration time and transmittance is proposed to compensate the calibration error caused by the change of these two factors. Experiments confirm that the accuracy of the proposed calibration algorithm can reach about 1 % under the conditions of varying integration time and transmittance, which is effectively applicable to high dynamic range infrared imaging applications.

SNPP VIIRS RSB on-orbit radiometric calibration algorithms Version 2.0 and the performances, part 2: the performances

SNPP VIIRS RSB on-orbit radiometric calibration algorithms Version 2.0 and the performances, part 2: the performances

Relative radiometric calibration of yaw data without calibration field of hyperspectral images based on harmonic analysis

ABSTRACT Radiometric calibration of satellite sensor could be divided into absolute radiometric calibration and relative radiometric calibration. Relative radiometric calibration can greatly reduce the impact of the sensor’s instability due to many factors like failure to perform calibration experiments or satellite post-operative attenuation. One of the methods is to use the 90° yaw data for relative radiation calibration, where the camera or satellite rotates by 90° so that the linear charge-coupled device (CCD) detector is parallel to the flight direction and sequentially passes through the ground uniform field to obtain the same radiance to achieve the satellite in order to achieve relative radiometric calibration of satellite sensor and eliminate stripe phenomenon in image. The orbita hyperspectral satellites (OHS) are commercial hyperspectral remote sensing satellites with the largest image width and the highest spatial resolution in China. It has realized the operation of multiple hyperspectral satellites network for the first time. However, there are still problems such as inaccurate calculation of radiation calibration parameters, difficulty in realizing uniform field ground, and difficulty in achieving full dynamic calibration of the sensor. In this study, the hyperspectral images acquired by OHS satellites were taken as the research object to propose a method to achieve field-free relative radiometric calibration based on harmonic analysis of yaw data. This method combines the advantages of harmonic analysis technology and the least squares theory and is applied to the relative radiation calibration of hyperspectral yaw data. It is called the harmonic analysis radiometric calibration (HARC) algorithm. First, HARC algorithm performed the first-order forward and reverses harmonic analysis on the 86° yaw data of OHS satellites which were pre-processed into the data of the conventional image mode to obtain the theoretical value of the pre-processed yaw data. Then, the actual radiance value of yaw data in column direction would be fitted to the theoretical value using the least squares theory to calculate the offset and gain of radiometric calibration parameter after eliminating the high and low radiance values in yaw data. Finally, the offset and gain parameters were used to carry out relative radiometric calibration on conventional push-broom satellite image. The comparative analysis of the test showed that relative radiometric calibration of all band images of six pieces of CCD arrays in the hyperspectral sensor of OHS satellites was realized based on yaw data without uniform ground calibration field. The HARC algorithm proposed in this paper can overcome the inaccurate calculation of calibration parameters caused by the yaw angle less than 90°. It not only retains the image detail information but also effectively removes various types of thick and thin stripe noise in the sweep direction, and is not limited by the different bands. The algorithm has good universality in applications on various bands. Qualitative and quantitative comparison analyses were conducted between HARC algorithm and classical relative radiometric calibration methods, and the corrected image has a great improvement in image quality and sharpness compared with the original image. The effect of stripe removal and the accuracy of radiation correction of the HARC algorithm are superior to the classical relative radiation calibration method.

FY-3D HIRAS Radiometric Calibration and Accuracy Assessment

The High-Spectral Infrared Atmospheric Sounder (HIRAS) is a Fourier transform spectrometer onboard the fourth polar-orbiting FengYun 3D satellite (FY-3D). The FY-3D HIRAS provides interferogram measurements of Earth view radiance spectra in three infrared spectral bands at 29 cross-track positions, each with a $2 \times 2$ array of field of views (FOVs). The HIRAS level 1 radiance data cover the spectral bands from 650 to 1135 cm−1 [long-wave (LW) band], 1210 to 1750 cm−1 [mid-wave (MW) band], and 2155 to 2550 cm−1 [short-wave (SW) band] with a spectral resolution of 0.625 cm−1. The radiometric calibration algorithm and the methods of refining the nonlinearity (NL) and the polarization correction coefficients on orbit are summarized in this article. The NL correction coefficients are derived by minimizing the spread of the responsivity functions derived from the measurements of the internal calibration target with varying temperatures. The polarization correction coefficients are derived from the cold space observations and the routine Earth scene measurements. The radiometric accuracy is assessed by comparing the HIRAS measurements to the collocated Cross-track Infrared Sounder (CrIS) observations and radiance simulations. The results show that, compared to CrIS, the radiometric differences are about 0.3 and 0.7 K for the LW and MW bands, respectively, and 0.5 K for the CO absorption and window regions in the SW band. The consistency of the radiometric calibration among the four FOVs is estimated to be within 0.2 K for most of the spectral domain. Some remaining issues for the FY-3D HIRAS are also discussed.

Calibration algorithm for cooled mid-infrared systems considering the influences of ambient temperature and integration time.

Midwave infrared systems with cooled detectors are generally used for high-precision or quantitative measurement, such as radiometry and thermometry. As a basis of these applications, radiometric calibration aims to obtain the relationship between the infrared images and the incident radiant flux generated by the scene or targets. Conventional radiometric calibration algorithms do not take the influences of integration and ambient temperature into consideration. As a consequence, the accuracy of calibration deteriorates whenever the temperature or the integration time varies. To solve this problem, we analyzed the effects of integration time and ambient temperature on coefficients of the radiometric calibration formula by theoretical and experimental analysis. Then, a radiometric calibration method is deduced to remove the variation of integration time and ambient temperature on the accuracy of calibration and radiometry. Several radiometric calibration experiments were conducted using a midwave infrared camera inside a chamber with controllable temperature. The results indicate that the proposed calibration algorithm is more effective and accurate, compared with conventional calibration methods, in complicated working conditions with variable integration times and ambient temperatures.

UAV Remote Sensing Image Mosaic and Its Application in Agriculture

UAV remote sensing image has the characteristics of higher spatial resolution, fine timeliness and high flexibility. It is widely used in many fields such as agriculture, forestry, soil resources and so on. Especially in agriculture, it plays an important role in information acquisition of agricultural production and agricultural condition monitoring. In the experiment, high-definition digital camera and multi-spectral camera are used to capture the visible light and near-infrared remote sensing image. Two pieces of 3m*3m calibration cloth is used for radiometric calibration and SIFT algorithm was used for image mosaic. This paper discusses the application of remote sensing image in agriculture, including rice lodging monitoring, diseases and pests monitoring, crop growth monitoring and crop nutrient diagnosis. The results show that UAV remote sensing provides an effective means for agricultural condition information acquisition, and has wide application prospect.

Inter-Band Radiometric Comparison and Calibration of ASTER Visible and Near-Infrared Bands

The present study evaluates inter-band radiometric consistency across the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) visible and near-infrared (VNIR) bands and develops an inter-band calibration algorithm to improve radiometric consistency. Inter-band radiometric comparison of current ASTER data shows a root mean square error (RMSE) of 3.8%–5.7% among radiance outputs of spectral bands due primarily to differences between calibration strategies of the NIR band for nadir-looking (Band 3N) and the other two bands (green and red bands, corresponding to Bands 1 and 2). An algorithm for radiometric calibration of Bands 2 and 3N with reference to Band 1 is developed based on the band translation technique and is used to obtain new radiometric calibration coefficients (RCCs) for sensor sensitivity degradation. The systematic errors between radiance outputs are decreased by applying the derived RCCs, which result in reducing the RMSE from 3.8%–5.7% to 2.2%–2.9%. The remaining errors are approximately equal to or smaller than the intrinsic uncertainties of inter-band calibration derived by sensitivity analysis. Improvement of the radiometric consistency would increase the accuracy of band algebra (e.g., vegetation indices) and its application. The algorithm can be used to evaluate inter-band radiometric consistency, as well as for the calibration of other sensors.

THERMAL INFRARED INSPECTION OF ROOF INSULATION USING UNMANNED AERIAL VEHICLES

Abstract. UAVs equipped with high-resolution thermal cameras provide an excellent investigative tool used for a multitude of building-specific applications, including roof insulation inspection. We have presented in this study a relative thermographic calibration algorithm and a superpixel Markov Random Field model to address problems in thermal infrared inspection of roof insulation using UAVs. The relative thermographic radiometric calibration algorithm is designed to address the autogain problem of the thermal camera. Results show the algorithm can enhance the contrast between warm and cool areas on the roof surface in thermal images, and produces more constant thermal signatures of different roof insulations or surfaces, which could facilitate both visual interpretation and computer-based thermal anomaly detection. An automatic thermal anomaly detection algorithm based on superpixel Markov Random Field is proposed, which is more computationally efficient than pixel based MRF, and can potentially improve the production throughput capacity and increase the detection accuracy for thermal anomaly detection. Experimental results show the effectiveness of the proposed method.

Processing and Calibration of Submillimeter Fourier Transform Radiometer Spectra From the RHUBC-II Campaign

The Radiative Heating in Underexplored Bands Campaign-II, conducted in 2009 from a high-altitude site in northern Chile, combined ground-based radiometry with radiosonde measurements of atmospheric state, for the purpose of testing atmospheric radiation models under conditions strongly influenced by water vapor in the middle to upper troposphere. A suite of broadband Fourier transform spectrometers (FTSs) measured the entire terrestrial thermal radiance spectrum from 1000- to 3.3-μm wavelength. The submillimeter portion of the spectrum, from 1000 to 85 μm (300-3500 GHz) was covered by a polarizing FTS referred to as the Smithsonian Astrophysical Observatory (SAO) FTS. Here, we describe data processing and radiometric calibration algorithms for this instrument. These include correction of interferograms for periodic sampled lag error, development of a temperature-dependent instrument calibration model, and principal component analysis of the complete set of spectra acquired during the campaign.

Calibration of Suomi national polar‐orbiting partnership advanced technology microwave sounder

The Suomi National Polar‐Orbiting Partnership (NPP) satellite was launched on 28 October 2011 and carries the Advanced Technology Microwave Sounder (ATMS) on board. ATMS is a cross‐track scanning instrument observing in 22 channels at frequencies ranging from 23 to 183 GHz, permitting the measurements of the atmospheric temperature and moisture under most weather conditions. In this study, the ATMS radiometric calibration algorithm used in the operational system is first evaluated through independent analyses of prelaunch thermal vacuum data. It is found that the ATMS peak nonlinearity for all the channels is less than 0.5 K, which is well within the specification. For the characterization of the ATMS instrument sensitivity or noise equivalent differential temperatures (NEDT), both standard deviation and Allan variance of warm counts are computed and compared. It is shown that NEDT derived from the standard deviation is about three to five times larger than that from the Allan variance. The difference results from a nonstationary component in the standard deviation of warm counts. The Allan variance is better suited than the standard deviation for describing NEDT. In the ATMS sensor brightness temperature data record (SDR) processing algorithm, the antenna gain efficiencies of main beam, cross‐polarization beam, and side lobes must be derived accurately from the antenna gain distribution function. However, uncertainties remain in computing the efficiencies at ATMS high frequencies. Thus, ATMS antenna brightness temperature data records (TDR) at channels 1 to 15 are converted to SDR with the actual beam efficiencies whereas those for channels 16 to 22 are only corrected for the near‐field sidelobe contributions. The biases of ATMS SDR measurements to the simulations are consistent between GPS RO and NWP data and are generally less than 0.5 K for those temperature‐sounding channels where both the forward model and input atmospheric profiles are reliable.

Robust Radiometric Calibration and Vignetting Correction

In many computer vision systems, it is assumed that the image brightness of a point directly reflects the scene radiance of the point. However, the assumption does not hold in most cases due to nonlinear camera response function, exposure changes, and vignetting. The effects of these factors are most visible in image mosaics and textures of 3D models where colors look inconsistent and notable boundaries exist. In this paper, we propose a full radiometric calibration algorithm that includes robust estimation of the radiometric response function, exposures, and vignetting. By decoupling the effect of vignetting from the response function estimation, we approach each process in a manner that is robust to noise and outliers. We verify our algorithm with both synthetic and real data which shows significant improvement compared to existing methods. We apply our estimation results to radiometrically align images for seamless mosaics and 3D model textures. We also use our method to create high dynamic range (HDR) mosaics which are more representative of the scene than normal mosaics.

Radiometric and spectral performance and calibration of the GHz bands of EOS MLS

This paper describes radiometric performance and prelaunch radiometric and spectral calibrations of the GHz component of the Microwave Limb Sounder (MLS) experiment on NASA's Aura spacecraft. Estimated systematic scaling uncertainties (3/spl sigma/) on limb port radiances are /spl sim/0.5% from radiometric calibration and /spl sim/0.5% to /spl sim/1% from spectral calibrations. Operational noise performance is consistent with prelaunch expectations, and in-orbit measurements to date indicate no changes in noise characteristics, and no observable calibration drifts. Spectral baseline has remained stable to /spl sim/20 mK since launch. Refinements to calibrations based on in-flight data are discussed, and radiometric calibration algorithms are described.

An Overview of the Visible and Infrared Scanner Radiometric Calibration Algorithm

Abstract The Visible and Infrared Scanner (VIRS) is one of the principal instruments on board the Tropical Rainfall Measuring Mission (TRMM) satellite. VIRS measurements provide cloud-top temperatures and structures that complement the rainfall rates derived from other TRMM sensors. The VIRS radiometric calibration algorithm converts the digital data downlinked from the instrument into spectral radiances. VIRS has five bands: one in the visible, one in the shortwave infrared, and three in the thermal infrared. The calibration algorithm treats each band in the same manner except that the visible and shortwave infrared bands do not respond to the thermal radiation emitted by the instrument, and these bands do not have the nonlinear responses with input radiance found in the thermal bands. The calibration coefficients for the visible and shortwave infrared bands were determined in the laboratory before launch. VIRS carries a reference blackbody that is used to update the calibration coefficients for the ther...

Prelaunch characteristics of the Moderate Resolution Imaging Spectroradiometer (MODIS) on EOS-AM1

The Moderate Resolution Imaging Spectroradiometer (MODIS), with 36 bands and 0.25-, 0.5-, and 1.0-km geometric instantaneous-fields-of-view (GIFOVs) at nadir, has completed system level testing and has been integrated onto the Earth Observing System (EOS)-AM1 spacecraft, which is slated for launch in 1998. Raytheon Santa Barbara Remote Sensing (SBRS), Goleta, CA, the MODIS developer, has performed extensive characterization and calibration measurements that have demonstrated a system that meets or exceeds most of NASA's demanding requirements. Based on this demonstrated capability, the MODIS Science Team, an international group of 28 land, ocean, atmosphere, and calibration remote-sensing scientists, has commenced delivery of algorithms that will routinely calculate 42 MODIS standard data products postlaunch. These products range from atmospheric aerosols, snow cover, and land and water surface temperature to leaf area index, ocean chlorophyll concentration, and sea ice extent, to name just a few. A description of the Science Team, including members' research interests and descriptions of their MODIS algorithms, can be found at the MODIS homepage (http://ltpwww.gsfc.nasa.gov/MODIS/MODIS.html). The MODIS system level testing included sufficient measurements in both ambient and thermal-vacuum environments to both demonstrate specification compliance and enable postlaunch implementation of radiometric calibration algorithms. The latter will include calculations to account for changes in response versus scan angle, response versus temperature, and response linearity. The system level tests also included performance verification of the onboard calibration systems, including the solar diffuser stability monitor (SDSM), the blackbody (BB), and the spectral radiometric calibration assembly (SRCA), which will enahle monitoring of MODIS performance postlaunch. Descriptions of these subsystems are also on the MODIS homepage.

Quadpolarization SAR Calibration Using Target Reciprocity

In this paper we present a novel algorithm for radiometric and polarimetric calibration of complex quadpolarization SAR data. It is based partially upon known targets in the image and partially upo...

The Seasat scanning multichannel microwave radiometer (SMMR): Radiometric calibration algorithm development and performance

Radiometric calibration algorithms for processing Seasat scanning multichannel microwave radiometer (SMMR) flight data are presented. An equation is derived which accounts for losses and reradiation in the microwave components and nonlinearities in the radiometer. The application of pre-launch calibration data to this derivation is described. A performance evaluation of the post-launch operation of the algorithm is presented, indicating temperature resolution of 0.63 K at 6.6 GHz and 1.39 K at 37 GHz.