CanopyGAN: A Wavelet-Enhanced GAN for image distortion correction in aircraft canopy

An efficient pipelined architecture for the real-time correction of barrel distortion in wide-angle camera images is presented in this paper. The distortion correction model is based on least-squares estimation to correct the nonlinear distortion in images. The model parameters include the expanded/corrected image size, the back-mapping coefficients, distortion center, and corrected center. The coordinate rotation digital computer (CORDIC) based hardware design is suitable for an input image size of 1028/spl times/1028 pixels and is pipelined to operate at a clock frequency of 40 MHz. The VLSI system will facilitate the use of a dedicated hardware that could be mounted along with the camera unit.

SummaryComplex distortions on calcium imaging often impair image registration accuracy. Here, we developed a registration algorithm, PatchWarp, to robustly correct slow image distortion for calcium imaging data. PatchWarp is a two-step algorithm with rigid and non-rigid image registrations. To correct non-uniform image distortions, it splits the imaging field and estimates the best affine transformation matrix for each of the subfields. The distortion-corrected subfields are stitched together like a patchwork to reconstruct the distortion-corrected imaging field. We show that PatchWarp robustly corrects image distortions of calcium imaging data collected from various cortical areas through glass window or gradient-index (GRIN) lens with a higher accuracy than existing non-rigid algorithms. Furthermore, it provides a fully automated method of registering images from different imaging sessions for longitudinal neural activity analyses. PatchWarp improves the quality of neural activity analyses and is useful as a general approach to correct image distortions in a wide range of disciplines.

In the process of the image generation, because the imaging system itself has differences in terms of nonlinear or cameraman perspective, the generated image will face the geometric distortion. Image distortion in general is also a kind of image degradation, which needs the geometric transform to correct each pixel position of the distorted images, so as to regain the original spatial relationships between pixels and the original grey value relation, and which is also one of important steps of image processing. From the point of view of the digital image processing, the distortion correction is actually a process of image restoration for a degraded image. In image processing, in terms of the image quality improvement and correction technology, namely the image restoration, with the wide expansion of digital image distortion correction processing applied, the processing technology of the image restoration has also become a research hotspot. In view of the image distortion issue, this paper puts forward the image distortion correction algorithm based on two-step and one-dimensional linear gray level interpolation to reduce the computation complexity of the bilinear interpolation method, and divide the distorted image into multiple quadrilaterals, and the area of the quadrilateral is associated with the distortion degree of the image in the given region, and express the region distortion of each quadrilateral with the bilinear model, thus determining parameters of bilinear model according to the position of the quadrilateral vertex in the target image and the distorted image. Experiments show that such algorithm in this paper can meet the requirements of distortion correction of most lenses, which can accurately extract the distorted edge of the image, thus making the corrected image closer to the ideal image.

Microscopic vision modeling method by direct mapping analysis for micro-gripping system with stereo light microscope

Fusion of preoperative and intraoperative magnetic resonance imaging (iMRI) studies during stereotactic navigation may be very useful for procedures such as tumor resections but can be subject to error because of image distortion. To assess the impact of 3-dimensional (3D) vs 2-dimensional (2D) image distortion correction on the accuracy of auto-merge image fusion for stereotactic neurosurgical images acquired with iMRI using a head phantom in different surgical positions. T1-weighted intraoperative images of the head phantom were obtained using 1.5T iMRI. Images were postprocessed with 2D and 3D image distortion correction. These studies were fused to T1-weighted preoperative MRI studies performed on a 1.5T diagnostic MRI. The reliability of the auto-merge fusion of these images for 2D and 3D correction techniques was assessed both manually using the stereotactic navigation system and via image analysis software. Eight surgical positions of the head phantom were imaged with iMRI. Greater image distortion occurred with increased distance from isocenter in all 3 axes, reducing accuracy of image fusion to preoperative images. Visually reliable image fusions were accomplished in 2/8 surgical positions using 2D distortion correction and 5/8 using 3D correction. Three-dimensional correction yielded superior image registration quality as defined by higher maximum mutual information values, with improvements ranging between 2.3% and 14.3% over 2D correction. Using 3D distortion correction enhanced the reliability of surgical navigation auto-merge fusion of phantom images acquired with iMRI across a wider range of head positions and may improve the accuracy of stereotactic navigation using iMRI images.

The reverse ray-tracing method has become a well-known technique to correct the dynamic imaging distortion caused by the Risley-prism imaging system due to its precision and computational efficiency. However, the reverse ray-tracing method is sensitive to equipment error, which seriously degrades the quality of distortion correction when using a prism with a large wedge angle or a camera with a large field of view. We optimize the distortion correction method utilizing reverse ray tracing. In addition, we propose a distortion correction model with error parameters to investigate the influence of prism orientation error, prism tilt error, prism parameter error, and model simplification errors on the correction accuracy. The work on the optimized model clearly indicates the obvious image distortion introduced by different kinds of errors, including model error and systematic error. Furthermore, we propose an error parameter identification method to eliminate the negative results of error on the image correction. The simulation results show that the boresight pointing error and distortion correction error are reduced to about 1% of the initial value after 10 iterations, thus achieving high-precision imaging distortion correction and providing better data support for other subsequent applications.

New method for geometric calibration and distortion correction of conventional C-arm

To derive and implement a method for correcting spatial distortion caused by in vivo inhomogeneous static magnetic fields in echo-planar imaging (EPI). The reversed gradient method, which was initially devised to correct distortion in images generated by spin-warp MRI, was adapted to correct distortion in EP images. This method provides point-by-point correction of distortion throughout the image. EP images, acquired with a 3 T MRI system, of a phantom and a volunteer's head were used to test the correction method. Good correction was observed in all cases. Spatial distortion in the uncorrected images ranged up to 4 pixels (12 mm) and was corrected successfully. The correction was improved by the application of a nonlinear interpolation scheme. The correction requires that two EP images be acquired at each slice position. This increases the acquisition time, but an improved signal-to-noise ratio (SNR) is seen in the corrected image. The local SNR gain decreases with increasing distortion. In many EPI acquisition schemes, multiple images are averaged at each slice position to increase the SNR; in such cases the reversed gradient correction method can be applied with no increase in acquisition duration.

On-line implant reconstruction in HDR brachytherapy

Scanning electron microscopy (SEM) is a crucial technique for characterizing mechanical behavior at micro- and nano-scales. However, image distortions inherent to SEM can undermine the accuracy and reliability of these measurements, and thus, the distortion correction of image is essential for realizing precise measurement. In this study, a correction method for SEM image distortion based on sampled moiré has been developed to achieve high accuracy measurement of the deformation field. This method could effectively correct both time drift and spatial distortion of SEM image. Following the application of distortion correction, the average coordinate virtual displacement caused by spatiotemporal distortion can be corrected by over 80%. On this basis, nickel-based superalloy GH4169 was selected for microscale fatigue propagation experiments. An in-situ fatigue loading platform within the SEM was employed to observe the initiation and propagation of fatigue cracks in real time. The proposed correction method allowed for accurate measurement of microscale fatigue crack propagation parameters and quantitative characterization of the crack closure effect.

This thesis focuses on the research of multi-spectrum thermometry image distortion and non-uniformity correction based on the characteristic of single CCD transient imaging multi-spectrum thermometry. A distortion correction based on Zhang calibration is used to rectify the lens distortion. A non-uniformity correction combined two-point calibration with neural network is carried out to rectify the non-uniform images. Compare the images before and after correction, the distortion calibration method used in this thesis can decrease the error between the field image and the target location. The comparison of the images before and after non-uniformity correction illustrates that the non-uniformity correction used in this thesis can reduce the temperature measurement error caused by CCD pixel conformance differences observably.

Stereo light microscope (SLM) simulates stereo imaging principle of human eyes. Microscopic vision system based on SLM has become an important visual tool for micro measurement, micromanipulation, and microinjection. We develop a micromanipulation system based on SLM and present an image distortion correction method. We mainly correct two kinds of image distortions: lateral and vertical distortion. Distortion correction consists of two steps. First, a linear fitting algorithm for each row or column of target points is developed, and the fitting errors are calculated. If the fitting errors are smaller than a given threshold, the linear fitting results are kept and used. Otherwise polynomial fitting procedure will be used. Second, the parallelism of straight lines is corrected. The results show that a line in world coordinate frame (WCF) is not necessarily a straight line in image coordinate frame (ICF), or two parallel lines in WCF may be not parallel in ICF. Distortion correction can restore the parallel and linear relationship. For distorted left and right images, the magnitude of distortion exceeds 6 pixels and 4 pixels in the horizontal direction, and 1.2 pixels and 1.7 pixels in the vertical direction, respectively. After corrected, for left and right image, distortion can be reduced to 0.8 pixels and 0.7 pixels in the horizontal direction, and 0.96 pixels and 1.3 pixels in the vertical direction, respectively. The results show that distortion parameters obtained from the proposed method can effectively correct distorted images.

We aimed to show that correcting image distortion significantly affects brain volumetry using voxel-based morphometry (VBM) and to assess whether the processing of distortion correction reduces system dependency. We obtained contiguous sagittal T(1)-weighted images of the brain from 22 healthy participants using 1.5- and 3-tesla magnetic resonance (MR) scanners, preprocessed images using Statistical Parametric Mapping 5, and tested the relation between distortion correction and brain volume using VBM. Local brain volume significantly increased or decreased on corrected images compared with uncorrected images. In addition, the method used to correct image distortion for gradient nonlinearity produced fewer volumetric errors from MR system variation. This is the first VBM study to show more precise volumetry using VBM with corrected images. These results indicate that multi-scanner or multi-site imaging trials require correction for distortion induced by gradient nonlinearity.

Improving accuracy in x-ray image intensifier (XRII) image distortion correction has clinical impact in order to apply XRII images in a variety of clinical applications more reliably. This study aimed to develop and evaluate a new hybrid mathematic approximation method to correct geometric distortions of XRII images. The proposed hybrid method integrated an MLS (moving least-squares method) and an MBA (multilevel B-spline approximation) approach (MLSMBA). In the hybrid method, MLS is used to generate denser "virtual" data points on the basis of sparse original data points; MBA is applied to approximate an ultimate mapping function based on the generated and original data points. Using both computer-simulated and real XRII images, the authors compared the image distortion correction accuracy of the proposed method with those yielded using a number of previously developed and currently routinely used methods. The comparison methods include the traditional local and global approximation methods, an approach combining both local and global approximation methods, and an author's previously developed hybrid method by integrating MLS followed by another traditional least-square approximation (MLSILS). The image distortion correction accuracy was evaluated using mean-squared residual errors measured at control and intermediate points. In addition, the impact of pincushion distortion, sigmoidal distortion, local distortion, and control point localization errors on these methods was tested using computer-simulated image data. The experimental results using the computer-simulated data showed that unlike the traditional local and global approximation methods that are quite sensitive to pincushion and∕or sigmoidal distortion, the MLSMBA method was insensitive to these two types of common distortion depicted in XRII images. Similar to the MLSILS method, sensitivity of MLSMBA to local distortion was lower than or comparable with that of the traditional global approximation method. Although sensitivity of MLSMBA to control point localization errors was higher than that of the global approximation method, as long as the standard deviation of pixel displacement errors was smaller than 0.1 pixels, the overall distortion correction accuracy of MLSMBA remains higher than that of the other methods. By selecting a proper cutoff radius, accuracy of MLSMBA is also higher than that of the other methods (including MLSILS). Experiments on real XRII images yielded similar results. For example, processing results using one XRII image showed that residual error (0.248 ± 0.236 pixels) of MLSMBA was smallest as compared to that of the other methods, including two local approximation methods (0.456 ± 0.352 pixels and 0.370 ± 0.402 pixels), a global approximation method (0.422 ± 0.388 pixels), an approach combining local and global methods (0.389 ± 0.386 pixels), and MLSILS (0.255 ± 0.248 pixels). The MLSMBA method could be a better choice to correct geometric distortion of raw XRII images in the following conditions: (1) pincushion distortion, sigmoidal distortion, and local distortion exist simultaneously in the XRII images, (2) the number of original control points (landmarks) is limited, and (3) reusability of the correction mapping function is required.

A comparison of calibration methods for stereo fluoroscopic imaging systems