Image Width Research Articles

Accounting for intensity variation within pixels of Shack-Hartmann wavefront sensors

The accuracy of centroiding algorithms in Shack-Hartmann wavefront sensing is limited by the implicit approximation of uniform pixel illumination. Iterative centroiding algorithms are further limited by the consideration of full pixels to define the image domain for centroiding. Here, we demonstrate two practical and complementary approaches to mitigate both these sources of error. First, we consider partial or ‘fractional’ pixels to maintain centroiding area symmetry around the center of mass. Secondly, we propose methods to perform piece-wise polynomial interpolation to calculate intensity distribution within pixels, which is then used to estimate the centroid within each pixel area. This approach that accounts for intensity non-uniformity across pixels notably reduces centroid errors up to a factor of 5 across lenslet image widths ranging from 1.33 to 3.10 pixels full-width-half-maximum (FWHM). Consequently, wavefront sensing errors decrease from 14 % to 4 %, on average, for FWHM = 1.35 pixels, demonstrating a substantial benefit when the number of pixels per lenslet is minimized to enhance the signal-to-noise ratio or increase frame rate.

Application of vertical seismic profile multi-component data to tight sandstone gas reservoirs

Abstract Given the complex geological characteristics of the tight gas sandstone in the Shaximiao Formation of the Jurassic in the central Sichuan Basin, including its wide distribution, narrow width, and thin thickness, conventional surface seismic methods face significant challenges in reservoir delineation. To address this challenge, a vertical seismic profile (VSP) survey was conducted in the region in 2022, along with the simultaneous collection of 3D3C surface seismic data. This article mainly elaborates on a case study of using multi-component VSP technology to delineate tight sandstone gas reservoirs. By comparing the processed VSP imaging volume with the surface seismic imaging volume, it was discovered that the frequency width of the VSP image was 8 to 12 Hz higher than that of the surface seismic image. Utilizing the multi-component information in VSP data, it is feasible to more precisely delineate tight gas sandstones, thereby reducing the uncertainty of data interpretation. Based on the conventional data interpretation of these images, an innovative application suggests using the centroid frequency ratio of PSv to PP waves as an indicator for tight sandstone. The results show that this attribute has high sensitivity to this type of reservoir. Combining geological, drilling, and logging data, an interpretation template was established based on VSP data to interpret 3D3C surface seismic data and propose new drilling well locations. The conclusion is that the successful application of VSP technology cannot be achieved without the integration of multiple disciplines. The combined exploration technology of multi-component VSP and 3D3C surface seismic has been demonstrated to have high application value through practical application, significantly improving the success rate of gas wells and providing effective support for the exploration and development of tight sandstone gas reservoirs.

A Three-Step Computer Vision-Based Framework for Concrete Crack Detection and Dimensions Identification

Crack detection is significant to building repair and maintenance; however, conventional inspection is a labor-intensive and time-consuming process for field engineers. This paper proposes a three-step computer vision-based framework to quickly recognize concrete cracks and automatically identify their length, maximum width, and area in damage images. In step one, a region-based convolutional neural network (YOLOv8) is applied to train the crack localizing model. In step two, Gaussian filtering, Canny, and FindContours are integrated to extract the reference contour (a pre-designed seal) to obtain the conversion scale between pixels and millimeter-wise sizes. In step three, the recognized crack bounding box is cropped, and the ApproxPolyDP function and Hough transform are performed to quantify crack dimensions based on the conversion ratio. The developed framework was validated on a dataset of 4630 crack images, and the model training took 150 epochs. Results show that the average crack detection accuracy reaches 95.7%, and the precision of quantified dimensions is over 90%, while the error increases as the crack size grows smaller (increasing to 8% when the crack width is within 1 mm). The proposed method can help engineers to efficiently achieve crack information at building inspection sites, while the reference frame must be pre-marked near the crack, which may limit the scope of application scenarios. In addition, the robustness and accuracy of the developed image processing techniques-based crack quantification algorithm need to be further improved to meet the requirements in real cases when the crack is located within a complex background.

Digital pathology assessment of kidney glomerular filtration barrier ultrastructure in an animal model of podocytopathy.

Transmission electron microscopy (TEM) images can visualize kidney glomerular filtration barrier ultrastructure, including the glomerular basement membrane (GBM) and podocyte foot processes (PFP). Podocytopathy is associated with glomerular filtration barrier morphological changes observed experimentally and clinically by measuring GBM or PFP width. However, these measurements are currently performed manually. This limits research on podocytopathy disease mechanisms and therapeutics due to labor intensiveness and inter-operator variability. We developed a deep learning-based digital pathology computational method to measure GBM and PFP width in TEM images from the kidneys of Integrin-Linked Kinase (ILK) podocyte-specific conditional knockout (cKO) mouse, an animal model of podocytopathy, compared to wild-type (WT) control mouse. We obtained TEM images from WT and ILK cKO littermate mice at 4 weeks old. Our automated method was composed of two stages: a U-Net model for GBM segmentation, followed by an image processing algorithm for GBM and PFP width measurement. We evaluated its performance with a 4-fold cross-validation study on WT and ILK cKO mouse kidney pairs. Mean (95% confidence interval) GBM segmentation accuracy, calculated as Jaccard index, was 0.73 (0.70-0.76) for WT and 0.85 (0.83-0.87) for ILK cKO TEM images. Automated and manual GBM width measurements were similar for both WT (p=0.49) and ILK cKO (p=0.06) specimens. While automated and manual PFP width measurements were similar for WT (p=0.89), they differed for ILK cKO (p<0.05) specimens. WT and ILK cKO specimens were morphologically distinguishable by manual GBM (p<0.05) and PFP (p<0.05) width measurements. This phenotypic difference was reflected in the automated GBM (p<0.05) more than PFP (p=0.06) widths. These results suggest that certain automated measurements enabled via deep learning-based digital pathology tools could distinguish healthy kidneys from those with podocytopathy. Our proposed method provides high-throughput, objective morphological analysis and could facilitate podocytopathy research and translate into clinical diagnosis.

Synthetic-Aperture Radar Radio-Frequency Interference Suppression Based on Regularized Optimization Feature Decomposition Network

Synthetic-aperture radar (SAR) can work in all weather conditions and at all times, and satellite-borne radar has the characteristics of short revisiting period and large imaging width. Therefore, satellite-borne synthetic-aperture radar has been widely deployed, and the SAR images have been widely used in geographic mapping, radar interpretation, ship detection, and other fields. Satellite-borne synthetic-aperture radar is also susceptible to various types of intentional or unintentional interference during the imaging process, and because the interference is a direct wave, its power is much stronger than the wave reflected by targets. As a common interference pattern, radio-frequency interference widely exists in various satellite-borne synthetic-aperture radars, which seriously deteriorates SAR image quality. In order to solve the above problems, this paper proposes a feature decomposition network to suppress interference based on regularization optimization. The contributions of this work are as follows: 1. By analyzing the performance limitations of the existing methods, this work proposes a novel regularization method for radio-frequency interference suppression tasks. From the perspective of data distribution histograms and residual components, the proposed method eliminates the variable components introduced by common regularization, greatly reduces the difficulty of data mapping, and significantly improves its robustness and performance. 2. This work proposes a feature decomposition network, where the feature decomposition module contains two parts; one part only represents the interference signal, and the other part only represents the radar signal. The neurons representing the interference signal are discarded, and the neurons representing the radar signal are used as input for the subsequent network. A cosine similarity constraint is used to separate the interference from the network as much as possible. Finally, this method is validated on the MiniSAR dataset and Sentinel-1A dataset.

Leaf area estimation based on ANFIS using embedded system and PV panel

Leaf area is one of the important parameters for plant canopy development. It is used as an indicator closely related to plant growth in several studies on plant production. However, most leaf area meters used today are costly and rely on human observations. This situation may be limiting for researchers in terms of having proper leaf area measuring devices. The reliance on human-focused measurements leads to human errors. Digital scanners and cameras, digital image processing-based estimation methods, paper weighing, grid counting, regression equations, width and height correlation models, planimeters, laser optics, and handheld scanners can be used to determine leaf area. However, some of these methods are expensive and unnecessary for simple studies. Therefore, this study aims to design and implement an embedded system with a simpler, cheaper alternative to the currently used methods and devices, minimizing human errors. The proposed embedded system serves as a tool for measuring leaf area using a photovoltaic panel (PV) and an Adaptive Neuro-Fuzzy Inference System (ANFIS). In the study, geometric shapes with known areas are used as the learning data, and real plant leaves with known areas are used in the testing process. As a result, the prediction made by ANFIS is observed to have an accuracy of R2 = 0.99.

Relationships between internal solitary wave surface features in optical and SAR satellite images: Insights from remote sensing and laboratory

Internal solitary waves (ISWs) induce convergence and divergence of sea surface currents, manifesting as alternating bright and dark stripes in optical and synthetic aperture radar (SAR) remote sensing images. Although the relationship between ISW surface features in SAR images and ISW-induced surface currents has been extensively explored, it has not been clearly quantified in optical images. This study contrasts the surface features of the same ISWs using optical and SAR images with short time intervals and statistically analyses the 450 ISW stripe widths in the northern South China Sea and the Andaman Sea. The results demonstrate that the ISW surface features in optical and SAR images differ, with the ISW stripe widths of SAR images being 0.83 times those of optical images. Laboratory experiments are conducted to simulate the ISW surface features of optical and SAR images, which exhibit a consistent quantitative relationship with remote sensing results. Further experiments reveal that the ISW-induced free surface displacement is the cause of the differences in the ISW surface features between optical and SAR images. This research provides support for broader quantitative applications of optical remote sensing images.

Transrectal ultrasonographic assessment of the fetal proximal phalanx: A new tool to assess fetal age and bone development in horses

Fetal age in Quarter Horses can be predicted within 2 weeks from 100- to 200- days of gestation using femur length, biparietal diameter (cranium diameter) and eye approximated volume. However, as pregnancy advances, the femur and cranium become too large to be imaged in their entirety using ultrasound and the corresponding biometric parameters can no longer be measured. In this longitudinal study, the proximal phalanx (P1) was evaluated as a novel biometric parameter for late gestation to predict fetal age and bone maturation. Transrectal ultrasound was performed in ten pregnant mares with known ovulation dates, every two weeks from 240- days of gestation until parturition. P1 was imaged in 69 % of the examinations. Inability to image P1 was due to obstructive positioning such as carpal or fetlock flexion, or posterior presentation of the fetus. Advancing fetal age did not affect visibility of P1. P1 length correlated significantly with days of gestation and a correlation equation was established: y = 0.3837x -69.55 where y is the predicted value of P1 length and x is the day of gestation (with day 0 being the day of ovulation). When P1 length was equal to or larger than the width of the ultrasound image (52.5 mm), 90 % of mares (9/10) were above 300- days of gestation. Ossification of the proximal and distal epiphysis of P1 typically appeared between 277- and 303 -days of gestation (mean: 288 days). The proximal epiphysis did not close before parturition whereas the distal one closed between 306- and 333-days of gestation (mean: 320 days). P1 epiphyseal appearance and closure occurred chronologically reflecting bone maturation. Radiographic findings at birth and prenatal ultrasound findings were in agreement, apart from timing of P1 distal epiphyseal closure. In conclusion, P1 length can be used as a new fetal biometric parameter to assess fetal age and growth after 240- days of gestation. The knowledge of P1 bone maturation process in utero as a marker for fetal bone development, may also be valuable in clinical decision-making when considering inducing parturition in the mare.

A heat grid-driven method for generation of satellite observation tasks

Managing numerous observation requirements on a large-scale satellite constellation is arduous for satellite control departments. Concurrently, achieving fast and effective task scheduling necessitates autonomous observation task generation. To address this issue, we proposed a novel method combined with Observation Requirements Heat Grid Model (ORHGM) and a Grid Aggregation Algorithm Based on Field of View Exploration (GAAFVE). Firstly, we define a uniform description of the observation requirements for various target types by devising a heat grid model predicated on geographic grid segmentation. Experimental outcomes reveal that our uniform model saves up to 31.93% of the observation tasks for fulfilling identical requirements by independent task generation for various target types. Secondly, based on this model, an autonomous task generation is completed by GAAFVE. Under the constraints regarding satellite imaging width, our algorithm facilitates heat grid search for non-connected regions and demonstrates superiority in computing time compared to other clustering-based task algorithms. The proposed method can allow managing large-scale observation requirements to be completed relatively quickly for satellite control departments. This method can also be extended to task generation in other multi-agent systems beyond satellites, such as the automatic generation of multi-UAV disaster reconnaissance tasks.

Experimental Determination of the Transverse Width and Position of the Virtual Images Produced by Thin Lenses and a Plane Mirror with Smartphone Photography

Experimental Determination of the Transverse Width and Position of the Virtual Images Produced by Thin Lenses and a Plane Mirror with Smartphone Photography

A Modified Frequency Nonlinear Chirp Scaling Algorithm for High-Speed High-Squint Synthetic Aperture Radar with Curved Trajectory

The imaging of high-speed high-squint synthetic aperture radar (HSHS-SAR), which is mounted on maneuvering platforms with curved trajectory, is a challenging task due to the existence of 3-D acceleration and the azimuth spatial variability of range migration and Doppler parameters. Although existing imaging algorithms based on linear range walk correction (LRWC) and nonlinear chirp scaling (NCS) can reduce the range–azimuth coupling of the frequency spectrum (FS) and the spatial variability of the Doppler parameter to some extent, they become invalid as the squint angle, speed, and resolution increase. Additionally, most of them ignore the effect of acceleration phase calibration (APC) on NCS, which should not be neglected as resolution increases. For these issues, a modified frequency nonlinear chirp scaling (MFNCS) algorithm is proposed in this paper. The proposed MFNCS algorithm mainly includes the following aspects. First, a more accurate approximation of range model (MAARM) is established to improve the accuracy of the instantaneous slant range history. Second, a preprocessing of the proposed algorithm based on the first range compression, LRWC, and a spatial-invariant APC (SIVAPC) is implemented to eliminate most of the effects of high-squint angle and 3-D acceleration on the FS. Third, a spatial-variant APC (SVAPC) is performed to remove azimuth spatial variability introduced by 3-D acceleration, and the range focusing is accomplished by the bulk range cell migration correction (BRCMC) and extended secondary range compression (ESRC). Fourth, the azimuth-dependent characteristics evaluation based on LRWC, SIVAPC, and SVAPC is completed to derive the MFNCS algorithm with fifth-order chirp scaling function for azimuth compression. Consequently, the final image is focused on the range time and azimuth frequency domain. The experimental simulation results verify the effectiveness of the proposed algorithm. With a curved trajectory, HSHS-SAR imaging is carried out at a 50° geometric squint angle and 500 m × 500 m imaging width. The integrated sidelobe ratio and peak sidelobe ratio of the point targets at the scenario edges approach the theoretical values, and the range-azimuth resolution is 1.5 m × 3.0 m.

A Multi-Hyperspectral Image Collaborative Mapping Model Based on Adaptive Learning for Fine Classification

Hyperspectral (HS) data, encompassing hundreds of spectral channels for the same area, offer a wealth of spectral information and are increasingly utilized across various fields. However, their limitations in spatial resolution and imaging width pose challenges for precise recognition and fine classification in large scenes. Conversely, multispectral (MS) data excel in providing spatial details for vast landscapes but lack spectral precision. In this article, we proposed an adaptive learning-based mapping model, including an image fusion module, spectral super-resolution network, and adaptive learning network. Spectral super-resolution networks learn the mapping between multispectral and hyperspectral images based on the attention mechanism. The image fusion module leverages spatial and spectral consistency in training data, providing pseudo labels for spectral super-resolution training. And the adaptive learning network incorporates spectral response priors via unsupervised learning, adjusting the output of the super-resolution network to preserve spectral information in reconstructed data. Through the experiment, the model eliminates the need for the manual setting of image prior information and complex parameter selection, and can adjust the network structure and parameters dynamically, eventually enhancing the reconstructed image quality, and enabling the fine classification of large-scale scenes with high spatial resolution. Compared with the recent dictionary learning and deep learning spectral super-resolution methods, our approach exhibits superior performance in terms of both image similarity and classification accuracy.

Automatic Recognition and Quantification Feeding Behaviors of Nursery Pigs Using Improved YOLOV5 and Feeding Functional Area Proposals.

A novel method is proposed based on the improved YOLOV5 and feeding functional area proposals to identify the feeding behaviors of nursery piglets in a complex light and different posture environment. The method consists of three steps: first, the corner coordinates of the feeding functional area were set up by using the shape characteristics of the trough proposals and the ratio of the corner point to the image width and height to separate the irregular feeding area; second, a transformer module model was introduced based on YOLOV5 for highly accurate head detection; and third, the feeding behavior was recognized and counted by calculating the proportion of the head in the located feeding area. The pig head dataset was constructed, including 5040 training sets with 54,670 piglet head boxes, and 1200 test sets, and 25,330 piglet head boxes. The improved model achieves a 5.8% increase in the mAP and a 4.7% increase in the F1 score compared with the YOLOV5s model. The model is also applied to analyze the feeding pattern of group-housed nursery pigs in 24 h continuous monitoring and finds that nursing pigs have different feeding rhythms for the day and night, with peak feeding periods at 7:00-9:00 and 15:00-17:00 and decreased feeding periods at 12:00-14:00 and 0:00-6:00. The model provides a solution for identifying and quantifying pig feeding behaviors and offers a data basis for adjusting the farm feeding scheme.

CREATIVE PROCESSES OF EMOTIONAL IMAGES: THE EFFECTS OF ASPECT RATIO ON THE EMOTIONAL AND AESTHETIC PROPERTIES OF IMAGES

Proportions are one of the primary components of successful image composition during the visual art creation process, which, in turn, is determinant of the variety of effects of images on the viewer, including emotional reactions, attention, and aesthetic preference. The importance of image width and height ratio is especially visible in the current trend to adopt the widest possible screens in a variety of modern creative media applications: photo, video, computer games, etc. In the present study emotional and aesthetic evaluations of the three most popular aspect ratios that are used in digital media devices were compared. This was achieved by assessing emotional arousal and valence ratings together with the interest and appeal evaluations of realistic photos presented in 4:3, 16:9, and 21:9 aspect ratios. The results demonstrated that the widest images did not have an inherent advantage – photos presented in the mid-wide aspect ratio of 16:9 could be considered as more effective, because they were rated as evoking the most positive emotional reactions and as the most liked pictures. This demonstrated that single design features can have an independent emotional effect, which needs to be considered in visual design aiming to evoke emotional reactions to the viewer.

Configuration Design Method of Mega Constellation for Low Earth Orbit Observation

The configuration optimization design of Low Earth Orbit observation mega constellation in complex space environment is a nonlinear problem that is difficult to solve analytically. In this paper, a constellation design method is proposed, considering satellite imaging width, formation flying of subgroup satellites, and global uniform coverage by payloads. Firstly, a configuration of satellites with the same subsatellite trajectory is proposed, and its orbital analytical expression under J2 perturbation is provided. Then, the relative motion feature points are extracted near the orbit of each satellite, and a group of uniform natural accompanying satellites are set to corresponding points. Afterwards, the orbit parameters of satellite and its companions are set as initial values, and the precise orbits under the High Precision Orbit Propagator model are solved in the neighborhood by using the Nondominated Sort Particle Swarm Optimization algorithm. Finally, the correctness of the configuration design method is verified by numerical simulation.

A multi-frame deformation velocity splicing method for wide-area InSAR measurement based on uncontrolled block adjustment: A case study of long-term deformation monitoring in Guangdong, China

Wide-area deformation measurements require multi-frame InSAR datasets for joint monitoring due to the limited swath width of SAR images. However, variations in the stability of reference points, error signal magnitude and distribution, and spatio-temporal filtering parameters result in different deformation rates between adjacent frames, leading to centimeter-level errors in the results. To obtain spatially consistent wide-area results, here we propose a multi-frame deformation velocity splicing method that combines InSAR datasets and block adjustment. We convert the line-of-sight deformation of each frame to vertical using an improved vertical deformation solution method. We construct an uncontrolled block adjustment model and use the results in the automatically identified overlapping areas as redundant observations to solve the deviation of each frame in a wide area. Finally, the multi-frame seamless results are sampled into a uniform spatial resolution cell network, to generate a wide-area deformation product with consistent reference. We validate the proposed method in Guangdong Province, China, covering an area of 1.96 × 105 km2. By correcting and fusing a total of 78 ALOS-1/PALSAR frames (2007–2010) and 11 Sentinel-1 frames (2015–2021) separately, we obtain the wide-area deformation products for Guangdong during the two periods. Compared with the original results, the inner precision of the ALOS-1/PALSAR and Sentinel-1 data is improved by 82.4% and 73.7%, respectively. Compared with GNSS, the accuracy of the corrected Sentinel-1 results is improved by more than 19%. The proposed method contributes to standardizing InSAR deformation production and facilitating the engineering application of wide-area InSAR measurements.

The Control of Lava Rheology on the Formation of Lunar Sinuous Rilles by Substrate Thermal Erosion: Topographic and Morphometric Relationships with Eruption Rates, Erosion Rates, Event Durations, and Erupted Magma Volumes

We describe a model of the fluid mechanics and thermodynamics of turbulent lava flows capable of thermally eroding sinuous rille channels on bodies without atmospheres. The model assumes Bingham plastic rheology for the lava and shows how the effects of radiant cooling and consequent crystallization change the rheology and control the point at which turbulence ceases. A correlation is found between magma volume eruption rate and the length and width of the eroded rille channel. Thus, simple measurements of rille length and width in images can provide reliable estimates of magma eruption rates. The model also predicts rille floor erosion rates, so that if rille depths are measured, eruption durations and erupted magma volumes can also be found. The model is applied in detail to six well-preserved lunar rilles and more generally to a published catalog of 214 lunar rilles. We find that rille-forming eruptions have magma volume eruption rates of a few times 104 m3 s−1, durations of up to 3 months, and erupted magma volumes up to ∼200 km3, consistent with theoretical predictions of basaltic magma ascent and eruption from deep mantle sources. The key requirement for rille formation, rather than mare lava flow deposit formation, is the turbulent eruption of a sufficiently large volume of low-viscosity magma at a sufficiently low eruption rate.

A General Relative Radiometric Correction Method for Vignetting Noise Drift

Due to the limitation of the number of sensor pixels, optical splicing is commonly used to improve the imaging width of remote sensing satellites, and this optical stitching can cause vignetting in the image data of adjacent sensors. The weak energy, low signal-to-noise ratio, and poor response stability of vignetting are key factors that restrict the relative radiometric correction of optical splicing remote satellites. This paper proposes a stability analysis method and a relative radiometric correction method for vignetting. First, we analyzed the stability of the response and the noise impact of vignetting. Massive data from the Jilin-1 GF03D satellites was used to analyze the stability of the response using the vignetting stability analysis method. Secondly, the data on the deep sea during nighttime (DDSN) of Jilin-1 GF03D satellites was used to obtain the characteristics of the sensors’ noise. Thirdly, by building a noise drift model, we calculated the coefficient of the noise drift according to its characteristics. Using the coefficient to eliminate the noise drift of each pixel in vignetting can improve the response stability of vignetting. The average response stability increased by 37.64% by this method. Finally, the automatic relative radiometric correction method was completed through histogram matching. Furthermore, we proposed color aberration metrics (CAMs) to evaluate the multi-spectral images after relative radiometric correction, and massive data from the 16 satellites of Jilin-1 GF03D was used to verify the effectiveness and generality. The experimental results show that the average CAM of the images increased by 15.97% using the proposed method compared to the traditional method.

Design and Implementation of Airborne Hyperspectral Camera Control and Data Storage System

With the great progress of hyperspectral imaging technology, airborne hyperspectral cameras have been widely used in the field of earth detection and remote sensing. However, with the increasing resolution of airborne hyperspectral cameras, the amount of data acquired is also growing explosive, The speed and accuracy in the transmission process are easily affected, which poses challenges to the real-time control and data acquisition and storage of airborne hyperspectral cameras. In this paper, a general airborne hyperspectral image acquisition and storage system is designed, which converts the hyperspectral data from the Cameralink interface into a high-speed serial PCIe data stream and realizes high-speed storage of image data. The image width is 2048 pixels, the number of spectral segments is 120, the pixel size is 12bit, and the maximum frame rate is 300 fps. The maximum transmission rate is 2048×120×12bit×300fps, and the data rate is 844Mbps. Based on this, we perform thermal analysis and vibration analysis of the system platform. Experimental results show that the system can achieve stable data transmission and storage, and the data is intact and reliable.

The high-resolution imaging science experiment (HiRISE) in the MRO extended science phases (2009–2023)

The Mars Reconnaissance Orbiter has been orbiting Mars since 2006 and has acquired >80,000 HiRISE images with sub-meter resolution, contributing to over 2000 peer-reviewed publications, and has provided the data needed to enable safe surface landings in key locations by several rovers or landers. This paper describes the changes to science planning, data processing, and analysis tools since the initial Primary Science Phase in 2006–2008. These changes affect the data used or requested by the community and how they should interpret the data. There have been a variety of complications to the dataset over the years, such as gaps in monitoring due to spacecraft and instrument issues and special events like the arrival of new landers or rovers on Mars or global dust storms. The HiRISE optics have performed well except for a period when temperature uniformity was perturbed, reducing the resolution of some images. The focal plane system now has 12 rather than 14 operational detectors. The first failure (2011) was a unit at the edge of the swath width, reducing image width by 10% rather than creating a gap. The recent (2023) failure was in the middle of the swath. An unusual problem with the analog-to-digital conversion of the signal (resulting in erroneous data) has worsened over time; mitigation steps so far have preserved full-resolution imaging over all functional detectors. Soon, full-resolution imaging will be narrowed to a subset of the detectors and there will be more 2 × 2 binned data. We describe lessons received for future very high-resolution orbital imaging. We continue to invite all interested people to suggest HiRISE targets on Mars via HiWish, and to explore the easy-to-use publicly available images.