Relative Calibration Method Research Articles

Research on on-orbit relative radiometric calibration method based on solar diffuse reflector hyperspectral camera

Abstract In the original image data obtained by optical remote sensing satellite sensors, there is stripe noise caused by inconsistent probe response, which will seriously affect the application effect and accuracy of the image. The importance of relative radiometric calibration is that it can eliminate the stripe noise in the image, thus improving the quality and clarity of the image. In this paper, a relative radiometric calibration method based on the data of a solar diffuse reflector downloaded from the satellite is proposed. The relative radiation calibration coefficient is calculated by using the least square method by obtaining the calibration image of the on-board diffuse reflector covering all the detectors. To verify the method proposed in this paper, the on-board relative radiometric calibration experiment is carried out by using the on-orbit hyperspectral camera of a terrestrial ecological carbon monitoring satellite, and the calibration effect of the calibration coefficient on the original image is tested, and the relative radiometric calibration accuracy is quantitatively analyzed. The experimental results show that the calibration coefficient can effectively eliminate the band noise of the original hyperspectral image. From the quantitative evaluation, the signal-to-noise ratio index of the corrected hyperspectral image is greater than 200, and the generalized noise index is better than 3%, which achieves a good calibration effect and meets the requirements of high-quality remote sensing image application. It provides a reliable guarantee for quantitative remote sensing applications during the satellite’s on-orbit operation.

A Multi-Task Convolutional Neural Network Relative Radiometric Calibration Based on Temporal Information

Due to the continuous degradation of onboard satellite instruments over time, satellite images undergo degradation, necessitating calibration for tasks reliant on satellite data. The previous relative radiometric calibration methods are mainly categorized into traditional methods and deep learning methods. The traditional methods involve complex computations for each calibration, while deep-learning-based approaches tend to oversimplify the calibration process, utilizing generic computer vision models without tailored structures for calibration tasks. In this paper, we address the unique challenges of calibration by introducing a novel approach: a multi-task convolutional neural network calibration model leveraging temporal information. This pioneering method is the first to integrate temporal dynamics into the architecture of neural network calibration models. Extensive experiments conducted on the FY3A/B/C VIRR datasets showcase the superior performance of our approach compared to the existing state-of-the-art traditional and deep learning methods. Furthermore, tests with various backbones confirm the broad applicability of our framework across different convolutional neural networks.

In-situ X-ray micro-CT quantitative analysis and modelling the damage evolution in granite rock

Micro-cracking of rock is important mechanism in underground engineering and subsurface energy extraction. Understanding and modeling microcrack evolution and coalescence, and the eventual macroscopic fracture propagation is still a challenge. A micro-mechanically motivated fracture model is developed based on observation and quantitative analysis of in-situ X-CT uniaxial compression test on brittle intact rock with the resolution of 11.98 μm. We performed uniaxial compression test on a micro-granite and acquired real-time X-CT images of crack development under different loadings to investigate cracking pattern, evolution of the crack network and geometric characteristics of the cracks. The experimental results show that the nucleation of isolated microcracks is the main damage pattern before failure. The evolution of damage is subtle under moderate loading but grows stably in density until the unstable coalescence of microcracks, followed by macro-scale failure. Moreover, the damage process is initially dominated by the development of inclined cracks; when failure is approached, the development of relatively more parallel cracks gradually become predominant, indicating the damage transition nature from shear mechanism to tensile mechanism. Based on the X-CT analysis, an improved physics-informed micro-mechanical sliding model is proposed. Compared with previous sliding models, the crack-crack interaction is improved so that this model can well characterize the abrupt failure process. The total surface area of cracks is used to quantify the damage evolution and a relative calibration method is presented. The simulation results show the stress–strain curve and damage evolution are consistent with the experimental results.

A self-adjusting method to generate daily consistent nighttime light data for the detection of short-term rapid human activities

Nighttime light (NTL) has become an emerging indicator of the magnitude and changes in human settlement and activities. A recently released Lunar-BRDF-corrected NTL product, Black Marble VNP46A2, with enhanced temporal (daily) and spatial (15 arc-second) resolutions, has the potential to monitor human reactions to short-term events with rapid light intensity variations. However, the VNP46A2 NTL exhibits unexpected large daily variations resulting from two residual errors (spatial observational coverage mismatch and angular effect), leading to difficulty in extracting true change signals of NTL time series. In this study, we developed a Self-adjusting method featuring Filter and Angular effect Correction (SFAC) to eliminate the two errors without any auxiliary data. The proposed adjusted-average filtering effectively reduced the mismatch error and enhanced data consistency with less “blooming effect” than other filtering methods. The normalized standard deviation of daily NTL was largely reduced in the selected airport areas after filtering. The variation caused by the angular effect has also been corrected by a relative calibration method using the 16 days' cycle of satellite view angles, which apparently decreases the dependence of the light intensity on the view angles. We further explored and found that the detectability of short-term rapid events (i.e., festival/event celebration with increased NTL and power outage with reduced NTL) using SFAC-corrected VNP46A2 outperformed the original product. More detailed information on rapid events and evolutions in small spaces is expected to be digested with the high-quality, SFAC-corrected daily consistent VNP46A2 NTL data.

An Improved Side-Slither Relative Radiometric Calibration Method for WFV Satellite: Taking HY1D CZI as an Example

An Improved Side-Slither Relative Radiometric Calibration Method for WFV Satellite: Taking HY1D CZI as an Example

Cross-medium imaging model and calibration method based on refractive optical path for underwater morphology measurement

Full-field optical morphology measurement methods are widely used in the shape measurement of underwater targets. The existing models and calibration methods in air could be invalid due to the refraction of light. To deal with these problems, this paper develops a cross-medium imaging model and a relative calibration method. In the modeling, the actual refraction optical path is considered when using arbitrary transparent structures. In the calibration, the accurate parameters of the model are first determined in the air environment and then updated by the refraction index replacement strategy. By using these methods, the accurate restoration of the morphology of objects in any medium is realized, and the inconvenience of underwater calibration process in prior methods can be avoided. The results of conducted experiments show that the accuracy of measurement can achieve 0.42%, which illustrates the validity of the proposed model and the precision of the proposed calibration method.

Evaluation of receiver calibration based on clock-steering for time–frequency transfer

Calibrating the global navigation satellite system (GNSS) time–frequency transfer system is crucial for accurate GNSS time–frequency transfer. The most commonly used relative calibration method relies on the common-clock to eliminate clock differences. However, it cannot eliminate the changes in clock signal reference point delay (REFDLY). The changes in REFDLY during calibration could not be ignored, especially for ordinary users in an unstable environment. To address this issue, we use the GNSS real-time single-difference time synchronization calibration based on clock-steering, which can detect the change in REFDLY. According to this method, the clock differences and REFDLY are eliminated simultaneously. We installed two GNSS antennas on the roof of the Xinghu Building of Wuhan University and designed a clock synchronization terminal to evaluate the performance of this method. The data were collected on Day of Year 152–156, 167–171, 222–226, 231–235, 244, 258, 260, and 262 in 2022. In accordance with the calibration results, the standard deviation better than 100 ps, and the stability reaches 10−15@10000s . Also, the time variance better than 60 ps, and the uncertainty uCAL better than 0.5 ns. Compared to the common-clock calibration, one of the most significant benefits is the elimination of REFDLY, which leads to decreased uncertainty and better stability over both the short-term and long-term.

A Relative Field Antenna Calibration Method Designed for Low-Cost GNSS Antennas by Exploiting Triple-Differenced Measurements

Performing the high-precision Global Navigation Satellite System (GNSS) applications with low-cost antennas is an up-and-coming research field. However, the antenna-induced phase biases, i.e., phase center corrections (PCCs), of the low-cost antennas can be up to centimeters and need to be calibrated in advance. The relative field antenna calibration method is easy to conduct, but the classical procedure entails integer ambiguity resolution, which may face the problem of low success rate under the centimeter-level PCCs. In this contribution, we designed a relative field calibration method suitable for the low-cost GNSS antennas. The triple-differencing operations were utilized to eliminate the carrier-phase ambiguities and then construct PCC measurements; the time-differencing interval was set to a relatively long time span, such as one hour, and the reference satellite was selected according to the angular distance it passed over during a time-differencing interval. To reduce the effect of significant triple-differencing noise, a weight setting method based on the area of a spherical quadrilateral was proposed for the spherical harmonics fitting process. The duration of the data collection with respect to GPS and BDS was discussed. The performance of the proposed method was assessed with real GPS and BDS observations and a variety of simulated phase patterns, showing that calibration results could be obtained with millimeter-level accuracy. The impact of cycle slip and elevation mask angle on the calibration results was also analyzed.

On-Orbit Relative Radiometric Calibration of the Bayer Pattern Push-Broom Sensor for Zhuhai-1 Video Satellites

The two video satellites of the second and third batch of Zhuhai-1 microsatellites (referred to as OVS-2A/3A) are operational with their hyperspectral satellites, which improves the data acquisi-tion capability of the Zhuhai-1 remote sensing satellite constellation. Contrary to the linear array push-broom hyperspectral satellites and plane array CCD video satellites, the OVS satellite is equipped with a planar array Bayer pattern sensor, which can obtain single-band grayscale images by push-broom imaging. Additionally, the Bayer color reconstruction algorithm can interpolate sensor data to provide RGB color band information. Therefore, for the Bayer pattern push-broom sensor, the relative calibration method of linear push-broom or array cameras cannot be directly applied. The radiometric calibration of the Bayer pattern push-broom imaging mode has become a matter of concern; therefore, this study developed a radiometric calibration method for the Bayer pattern push-broom sensor of the OVS satellite and verified its effectiveness and accuracy. OVS images were used to perform on-orbit relative radiometric calibration, and the calibration accu-racy, including streaking metrics and root-mean-square error, was better than 1%, meeting the specification requirements for the OVS satellite. Visually, after calibration correction, the streaking and striping noise of the Bayer images was removed, and the radiometric quality of the image was considerably improved, providing a good data basis for subsequent research in remote sensing applications.

Upgrade of the relative calibration methods and Bayesian inference processing for electron cyclotron emission radiometry

An upgraded local oscillator (LO) hopping calibration method based on a blackbody hot source and a perturbation analysis of the magnetic field difference method are introduced in this work. The blackbody hot source is used to evaluate the difference in the relative coefficients between the two LO hopping frequencies in the same channels. Then the coefficients are obtained by multiplying the LO hopping frequencies coefficients by LO hopping calibration coefficients. In this way, it is more flexible and stable than the in-situ calibration. The magnetic field difference method provides another calibration method to obtain the relative calibration coefficients of the electron cyclotron emission radiometers (ECE). In general, the magnetic field difference method needs two similar shots but with a difference of 2.1% (for HL-2M) in the magnetic field. Meanwhile, there are some errors because of the deviation of detection positions in the same channels between the two shots. For evaluating the calibration errors, the impact of the displacement, Te perturbation of the core region, and magnetic field difference has been discussed. The result shows that a larger magnetic field difference can improve the accuracy of the calibration. In the end, Bayesian inference has been utilized to evaluate the calibration coefficients and get the most probable calibration coefficients along with its the confidence interval.

Divergent evolutionary trajectories of bryophytes and tracheophytes from a complex common ancestor of land plants

The origin of plants and their colonization of land fundamentally transformed the terrestrial environment. Here we elucidate the basis of this formative episode in Earth history through patterns of lineage, gene and genome evolution. We use new fossil calibrations, a relative clade age calibration (informed by horizontal gene transfer) and new phylogenomic methods for mapping gene family origins. Distinct rooting strategies resolve tracheophytes (vascular plants) and bryophytes (non-vascular plants) as monophyletic sister groups that diverged during the Cambrian, 515–494 million years ago. The embryophyte stem is characterized by a burst of gene innovation, while bryophytes subsequently experienced an equally dramatic episode of reductive genome evolution in which they lost genes associated with the elaboration of vasculature and the stomatal complex. Overall, our analyses reveal that extant tracheophytes and bryophytes are both highly derived from a more complex ancestral land plant. Understanding the origin of land plants requires tracing character evolution across a diversity of modern lineages.

RELATIVE RADIOMETRIC CALIBRATION OF UAV IMAGES FOR IMAGE MOSAICKING

Abstract. Since UAV images are taken at a low altitude, compared to satellite or aerial images, they usually have narrow ground coverage. In order to use them over a large area of interest, it is essential to mosaic them into a large image. In addition, UAV images may have different brightness values at the same ground locations according to different weather conditions and relative position between sun and sensor at the time of photographing. To mosaic a large number of UAV images, it is essential to calibrate different brightness values through a relative radiometric calibration method. In this paper, we propose a relative radiometric calibration method of UAV images capable of reducing over-calibration and minimizing error transfers during image mosaicking. We applied a gain compensation technique to minimize the effect of exposure difference when generating mosaic image. We also applied an image blending technique to remove seamlines among adjacent images to merge. As a result, smooth mosaic images were generated without any noticeable brightness difference around seamlines. For quantitative validation, differences in brightness values in overlapping areas were calculated. The differences have been decreased after applying the proposed method. The results indicated that the proposed method could generate a natural mosaic image by correcting differences in brightness values and removing seamlines of UAV images. Our method has an advantage of being able to calibrate differences in brightness values only with DN values.

A least-squares method for simultaneous synchronization and relative calibration of overlapped videos

A least-squares method for simultaneous synchronization and relative calibration of overlapped videos

Research on localisation algorithm of large irregular workpiece for industrial robot

Aiming at the problem of large irregular workpiece positioning difficulty and large error, a new workpiece positioning method is presented. The research object of this paper is a large porous irregular workpiece with holes as the processing location of the workpiece. For this porous workpiece, a special calibration tool is designed and an appropriate calibration algorithm is selected to complete the calibration of the tool. And a relative calibration method is designed. This method uses a small number of holes on the workpiece as the calibration point, and combines the data of the 3D model of the workpiece to calculate the poses of all the holes of the workpiece. Using the robot teaching method, take the pose data of part of the hole on the workpiece, and calculate the calibration error by combining the hole pose obtained above. The experimental results show that the deviation meets the calibration requirements.

A Convolutional Neural Network-Based Relative Radiometric Calibration Method

Due to the degeneration problem of sensors, calibration becomes a prerequisite step to retrieve consistent satellite images, especially for the ones from long-term time series. Relative calibration is an economic manner to address the problem. Previous studies leverage the identified no-change pixels (NCPs) between two images for relative calibration. However, the identification of NCPs itself is a very hard task and the inferior detection quality affects the performances significantly. Inspired by the great success of deep learning techniques, in this article, we first develop a convolutional neural network (CNN)-based relative calibration method, which bypasses the NCP detection. In particular, the ratio of sensor sensitivity coefficients at two time points is directly estimated by feeding the corresponding image pair into our developed CNN regressor. A polynomial function is fitted upon the estimated ratios in time series. We train the CNN regressor based on the multisite calibration results and then conduct experiments on FengYun-3A (FY-3A), FengYun-3B (FY-3B), and FengYun-3C (FY-3C). The results validate the effectiveness of the proposed method, and it outperforms state-of-the-art NCP-based methods.

Simulations of the source-range detector response for the fuel-loading process of the AP1000 cores

In this paper, the ex-core source-range detector response was simulated for AP1000 cores in its fuel-loading process by using a Monte Carlo code. Firstly, the current sensitivity coefficients of the ex-core source-range detectors have been calibrated by utilizing the experiments with single fuel assembly and the primary source loaded in the core. Secondly, both relative and absolute calibration methods have been applied and analyzed for the sensitivity coefficients calibration. Thirdly, the simulation values for the ex-core source-range response with fully loaded fuel have been validated by using the actual measurement of the first AP1000 cores in the world. Fourthly, the contribution of the 238U spontaneous fission to the ex-core source-range detector response has been studied. Through the numerical simulation results, the following observations can be obtained: 1) The relative calibration method is better than the absolute calibration method, especially when the ex-core source-range response is small. 2) Compared with the measurements, the relative deviation between the simulated and the measured values is within 14% for the two AP1000 cores at Sanmen Nuclear Power Plant. 3) The intensity of 238U spontaneous fission source accounts for 15% of the total source strength in the AP1000 core Unit 1, but the maximum change of response is only 0.02 cps, which is still insignificant for the ex-core detector response simulation in PWR.

Relative Radiometric Calibration Using Tie Points and Optimal Path Selection for UAV Images

As the use of unmanned aerial vehicle (UAV) images rapidly increases so does the need for precise radiometric calibration. For UAV images, relative radiometric calibration is required in addition to the traditional vicarious radiometric calibration due to the small field of view. For relative radiometric calibration, some UAVs install irradiance sensors, but most do not. For UAVs without them, an intelligent scheme for relative radiometric calibration must be applied. In this study, a relative radiometric calibration method is proposed to improve the quality of a reflectance map without irradiance measurements. The proposed method, termed relative calibration by the optimal path (RCOP), uses tie points acquired during geometric calibration to define the optimal paths. A calibrated image from RCOP was compared to validation data calibrated with irradiance measurements. As a result, the RCOP method produces seamless mosaicked images with uniform brightness and reflectance patterns. Therefore, the proposed method can be used as a precise relative radiometric calibration method for UAV images.

A novel calibration method for atmospheric NO3 radical via high reflectivity cavity

The NO3 radical is one of the important indicators of atmospheric oxidation capability at night, and its accurate detection has been extensively investigated. High reflectivity cavity instruments, such as cavity ring-down spectroscopy (CRDS) and cavity-enhanced absorption spectroscopy (CEAS), are generally employed for NO3 radical detection. However, sampling detection easily adsorbs radicals on surfaces, which causes complications and even additional loss. According to the chemical conversion relationship between NO3 radical and NO2, a method of absolute calibration different from the previous relative calibration method is applied by combining the CRDS and CEAS instruments for the NO3 radical and NO2, respectively. Experimental results show that the overall transmission efficiency of the NO3 radical for the CRDS instrument is approximately 75% ± 9% at a flow rate of 6.5 SLPM. Comparative experiments between the two methods are conducted to estimate the accuracy of this method. The achieved results indicate that absolute calibration is a reliable and feasible method for radical calibration in the laboratory. Furthermore, the absolute calibration method has the potential to realize accurate real-time calibration in field measurements.

High Quality Zenith Tropospheric Delay Estimation Using a Low-Cost Dual-Frequency Receiver and Relative Antenna Calibration

The recent release of consumer-grade dual-frequency receivers sparked scientific interest into use of these cost-efficient devices for high precision positioning and tropospheric delay estimations. Previous analyses with low-cost single-frequency receivers showed promising results for the estimation of Zenith Tropospheric Delays (ZTDs). However, their application is limited by the need to account for the ionospheric delay. In this paper we investigate the potential of a low-cost dual-frequency receiver (U-blox ZED-F9P) in combination with a range of different quality antennas. We show that the receiver itself is very well capable of achieving high-quality ZTD estimations. The limiting factor is the quality of the receiving antenna. To improve the applicability of mass-market antennas, a relative antenna calibration is performed, and new absolute Antenna Exchange Format (ANTEX) entries are created using a geodetic antenna as base. The performance of ZTD estimation with the tested antennas is evaluated, with and without antenna Phase Center Variation (PCV) corrections, using Precise Point Positioning (PPP). Without applying PCVs for the low-cost antennas, the Root Mean Square Errors (RMSE) of the estimated ZTDs are between 15 mm and 24 mm. Using the newly generated PCVs, the RMSE is reduced significantly to about 4 mm, a level that is excellent for meteorological applications. The standard U-blox ANN-MB-00 patch antenna, with a circular ground plane, after correcting the phase pattern yields comparable results (0.47 mm bias and 4.02 mm RMSE) to those from geodetic quality antennas, providing an all-round low-cost solution. The relative antenna calibration method presented in this paper opens the way for wide-spread application of low-cost receiver and antennas.

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.