Three-dimensional microstructure measurement by high-resolution fringe analysis for shadow moiré image by SEM

Abstract. Very high-resolution (∼10–100 m) surface soil moisture (SM) observations are important for applications in agriculture, among other purposes. This is the original goal of the S2MP (Sentinel-1/Sentinel-2-Derived Soil Moisture Product) algorithm, which was designed to retrieve surface SM at the agricultural plot scale by simultaneously using Sentinel-1 (S1) backscatter coefficients and Sentinel-2 (S2) NDVI (Normalized Difference Vegetation Index) as inputs to a neural network trained with Water Cloud Model simulations. However, for many applications, including hydrology and climate impact assessment at regional level, large maps with a high resolution (HR) of around 1 km are already a significant improvement with respect to most of the publicly available SM datasets, which have resolutions of about 25 km. In this study, the S2MP algorithm was adapted to work at 1 km resolution and extended from croplands to herbaceous vegetation types. A target resolution of 1 km also allows the evaluation of the interest in using NDVI derived from Sentinel-3 (S3) instead of S2. Two sets of SM maps at 1 km resolution were produced with S2MP over six regions of ∼104 km2 in Spain, Tunisia, North America, Australia, and the southwest and southeast regions of France for the whole year of 2019. The first set was derived from the combination of S1 and S2 data (S1 + S2 maps), while the second one was derived from the combination of S1 and S3 (S1 + S3 maps). S1 + S2 and S1 + S3 SM maps were compared to each other, to those of the 1 km resolution Copernicus Global Land Service (CGLS) SM and Soil Water Index (SWI) datasets, and to those of the Soil Moisture Active Passive (SMAP) + S1 product. The S2MP S1 + S2 and S1 + S3 SM maps are in very good agreement in terms of correlation (R≥0.9), bias (≤0.04 m3 m−3), and standard deviation of the difference (SDD≤0.03 m3 m−3) over the six domains investigated in this study. In a second step, the S1 + S3 S2MP maps were compared to the other HR maps. S1 + S3 SM maps are well correlated to the CGLS SM maps (R∼0.7–0.8), but the correlations with respect to the other HR maps (CGLS SWI and SMAP + S1) drop significantly over many areas of the six domains investigated in this study. The highest correlations between the HR maps were found over croplands and when the 1 km pixels have a very homogeneous land cover. The bias among the different maps was found to be significant over some areas of the six domains, reaching values of ±0.1 m3 m−3. The S1 + S3 maps show a lower SDD with respect to CGLS maps (≤0.06 m3 m−3) than with respect to the SMAP + S1 maps (≤0.1 m3 m−3) for all the six domains. Finally, all the HR datasets (S1 + S2, S1 + S3, CGLS, and SMAP + S1) were also compared to in situ measurements from five networks across five countries, along with coarse-resolution (CR) SM products from SMAP, SMOS, and the European Space Agency Climate Change Initiative (CCI). While all the CR and HR products show different bias and SDD, the HR products show lower correlations than the CR ones with respect to in situ measurements. The discrepancies in between the different HR datasets, except for the more simple land cover conditions (homogeneous pixels with croplands) and the lower performances with respect to in situ measurement than coarse-resolution datasets, show the remaining challenges for large-scale HR SM mapping.

A new method for computing the signal-to-noise ratio (SNR) of magnetic resonance images is presented. The proposed method is a "difference of images" based technique where two images are produced from one acquisition in which the readout direction field of view (FOV) and matrix size are doubled compared to the phase encode direction. Two "normal" unaliased FOV images are produced by splitting (undersampling) the even versus odd data points in the read direction into two separate raw data sets. After image reconstruction, conventional difference of images SNR computations are applied. [Signal defined as mean within signal producing region of interest (ROI) in one image, noise defined as standard deviation of the difference between the two images using the same signal ROI position and size, divided by sqrt(2) to account for the subtraction process.] This method combines the desirable minimal acquisition time of a single image acquisition technique and the superior noise quantification characteristics of the difference of images methodology. The proposed method is more robust against system drift than existing SNR difference of images methods because the two images are effectively acquired nearly simultaneously in time. This method is compatible with phased array coils and is useful for parallel image reconstruction analysis because it is very stable. This method produces results that can be made equivalent to, and compared with, other existing SNR methods with simple known scale factors, assuming the image noise follows theoretical expectations.

Brown adipose tissue (BAT) is a highly vascularized tissue that uptakes and oxidizes fatty acids from the circulation in response to a cold stimulus, resulting in thermogenesis. Tissue perfusion has been proposed as an approach to understand BAT metabolism, but current imaging techniques require invasive contrast or ionizing radiation. Power Doppler ultrasound imaging enables sensitive, high temporal resolution measures of the movement of blood as it perfuses a tissue without the need for contrast injections. The purpose of this study was to explore the utility of non‐contrast ultrasound perfusion imaging of human BAT during personalized cooling. Five healthy subjects [4 men; age: 31.8 ± 5.6 yrs.; body mass index: 22.5 ± 3.3 kg/m2; total body fat % (dual‐energy x‐ray absorptiometry scan): 22.9 ±7.0 %] underwent an individualized, perception‐based cooling protocol to stimulate BAT. Infrared thermography, a surrogate measure of BAT activity, and power Doppler ultrasound images were acquired over the right and left supraclavicular space, respectively, every five minutes in thermoneutrality (TN; duration: 15 min) and during cold exposure (CE) to the participant’s shiver threshold (duration: 58.3 ± 10.8 min; cooling dose: 319.7 ± 140.4 °C*min). Ultrasound images were post‐processed with a block‐wise, independent component analysis filter to analyze signal changes related to perfusion. BAT regions of interest were defined, and TN and CE conditions were compared as the mean ± standard deviation of the difference in the 95th percentile skin temperatures (infrared thermography) and the mean power Doppler signal (ultrasound). Supraclavicular skin temperature increased by 0.56 ± −0.21 °C (95% bootstrap confidence interval (CI): −0.57 to 1.72 °C), indicating a potential thermogenic response of BAT to individualized cooling (TN: 33.8 ± 1.1 °C vs. CE: 34.3 ± 0.9 °C). Similarly, the mean power Doppler signal increased by 11.6 ± 3.8 dB (95% CI: 3.2 to 19.4 dB) following cold exposure (TN: 46.8 ± 5.3 dB vs. CE: 58.3 ± 9.1 dB). These preliminary data demonstrate the feasibility of non‐contrast ultrasound perfusion imaging to detect the microvascular response of BAT to a cold stimulus in healthy adults. Power Doppler ultrasound imaging could prove useful when combined with existing noninvasive modalities (e.g. magnetic resonance imaging) to assess both the perfusion and metabolic substrate uptake response of BAT to potential obesity‐targeted therapies.Support or Funding InformationNIDDK/NIH R01‐DK‐105371, NCATS/NIH UL1‐TR000445

Phase-shifting shadow moire is an efficient technique for three-dimensional (3-D) shape measurement, but the technique is always suffered from the error of phase shifter. A three-frame random phase-shifting algorithm is proposed to relax the requirements of repeatability and accuracy of the phase shifter in a shadow moire system. The proposed method can act as a bridge between the three phase-shifting analysis methods and two-shot phase-shifting methods. The value of introduced arbitrary and unknown phase shift can be calculated by a determinate formula. The algorithm has the advantages of being free from the disturbance of background elimination and less computation. In addition, the proposed method is immune to nonsinusoidal fringe patterns and can be implemented easily in many applications. Both simulation and optical experimental results verify the feasibility of this method.

Blade is the key component of the aero-engine. In generally, it requires precise size and accurate shape, so the three-dimensional shape measurement of the blade is very important. Fringe projection profilometry is generally used to measure the 3D shape of an object, because of the advantages of non-contact operation, full-field acquisition, high resolution, and fast data processing. In this paper, 3D shape measurement method based on surface structured light that combination of gray-code and phase-shift projection is proposed. The wrapped phase of the blade is got by the four-step phase-shift method. In the projection process of the gray-code, due to the ambient light, different surface reflectance and surface physical discontinuous, the edge of gray-code becomes smooth, leading to decode error, so that the gray-code pattern must be binaried before decode. Through the accurate binarization of the blade gray-code pattern, the decoding cycle of the blade is achieved, and the unwrapped phase is achieved by phase unwrapping. Then the unwrapped phase difference between the blade and reference plane is got, the height of the blade can be obtained by the relationship between the phase difference and the height. The experimental and simulation results show that the proposed method can achieve a high precision, high speed and low cost 3D shape measurement of the blade. The measurement accuracy reaches 0.03 mm. The proposed method extends the reliability and practicality of the fringe projection profilometry.

Three-dimensional (3D) shape measurement of fringe projection profilometry (FPP) with high speed and accuracy is required in many applications. The measurement speed of FPP system is mainly limited by the low frame rate of pattern projection. Although defocusing binary patterns can be used to increase the measurement speed greatly, it will decrease the measurement depth. To this end, a novel triangular pattern generation method is proposed in this paper. By designing and projecting binary strip patterns with focused projector, images of triangular patterns can be then acquired with high frame rate. Fast and accurate 3D shape measurement can be finally obtained by using phase-shifting triangular patterns. Compared with the traditional sinusoidal patterns, the proposed method can improve the projection rate more than 4 times. Moreover, the proposed method will not decrease the measurement depth. Experimental results are given to confirm the validity of the proposed method.

Projector nonlinearity is a common problem for digital structured light-based three-dimensional (3-D) shape measurement techniques. A temporal-spatial binary encoding method is presented for the purpose of eluding it. We build a 3-D shape measurement scheme by combining our proposed method with phase measurement profiling. A standard sinusoidal fringe pattern is divided into more than two binary fringe patterns using specially designed temporal and spatial binary encoding rule based on intensity hierarchic quantification, and then are in-focus projected onto the measured object at a time sequence to reconstruct a frame phase-shifting fringe image. On account of the projected binary fringe pattern strictly consisting of zeros and ones, the influence of the projector nonlinearity on the measurement result can be effectively ruled out and simultaneously enables high-quality sinusoidality. In-depth investigations by theoretical analysis and experiments are conducted to demonstrate the performance of this method.

Modern endoscopes play an important role in diagnosing various gastrointestinal (GI) tract related diseases. The improved visual quality of endoscopic images can provide better diagnosis. This paper presents an efficient color image enhancement method for endoscopic images. It is achieved in two stages: image enhancement at gray level followed by space variant chrominance mapping color reproduction. Image enhancement is achieved by performing adaptive sigmoid function and uniform distribution of sigmoid pixels. Secondly, a space variant chrominance mapping color reproduction is used to generate new chrominance components. The proposed method is used on low contrast color white light images (WLI) to enhance and highlight the vascular and mucosa structures of the GI tract. The method is also used to colorize grayscale narrow band images (NBI) and video frames. The focus value and color enhancement factor show that the enhancement level in the processed image is greatly increased compared to the original endoscopic image. The overall contrast level of the processed image is higher than the original image. The color similarity test has proved that the proposed method does not add any additional color which is not present in the original image. The algorithm has low complexity with an execution speed faster than other related methods.

A non-contact arterial-induced skin vibration inspection system is implemented. This optical metrology system is constructed with shadow Moiré configuration and the fringe analysis algorithm. Developed with the Region of Interested (ROI) capturing technique and the Two-dimensional Wavelet Transform (2D-CWT) method, this algorithm is able to retrieve the height-correlated phase information from the shadow Moiré fringe patterns. Using a commercial video camera or a CMOS image sensor, this system could monitor the skin-vibration induced by the cyclic deformation of inner layered artery. The cross-sectional variation and the rhythm of heart cycle could be continuously measured for health monitoring purposes. The average vibration amplitude of the artery at the wrist ranges between 20 μm and 50 μm, which is quite subtle comparing with the skin surface structure. Having the non-stationary motion of human body, the traditional phase shifting (PS) technique can be very unstable due to the requirement of several frames of images, especially for case that artery is continuously pumping. To bypass this fundamental issue, the shadow Moiré technique is introduced to enhance the surface deformation characteristic. And the phase information is retrieved by the means of spectrum filtering instead of PS technique, which the phase is calculated from intensity maps of multiple images. The instantaneous surface can therefore be reconstructed individually from each frame, enabling the subtle arterial-induced skin vibration measurement. The comparative results of phase reconstruction between different fringe analysis algorithms will be demonstrated numerically and experimentally. And the electrocardiography (ECG) results will used as the reference for the validity of health monitoring potential of the non-contact arterial-induced skin vibration inspection system.

Phase unwrapping plays an important role in phase-based three-dimensional (3D) shape measurement. This paper proposes an effective pixel-wise phase unwrapping method without requiring additional fringe patterns. Firstly, compared with the geometric constraint-based (GCB) method which needs calibrate the fringe projection system and create a reference phase at the closest plane <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">z_min</i> within the measurement volume, the proposed method can adaptively and directly estimate the reference phase from the wrapped phase without system calibration and <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">z_min</i> estimation. Secondly, based on the finding that the slope angle of the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">z_min</i> plane ignored by the GCB method has significant impact on the measurement range, thus the phase gradients that highly correlates with the optimal slope angle are involved into reference phase estimation. The wrapped phase can be pixel-by-pixel unwrapped by comparing with the reference phase. Both simulations and experiments have been conducted to demonstrate the efficiency of the proposed method. Compared with traditional two-frequency method and phase-coding method, the proposed method can improve the measuring speed by 2 times. Experiment results show that the proposed method can effectively remove the phase unwrapping errors and achieve the mean absolute phase error of 0.0137 rad, which has obvious advantages relative to traditional methods.

Studies have reported that propagating waves can be generated in a finite one-dimensional structure by using two piezoelectric actuators. However it is not easy to generate stable and continuous propagating waves due to the finite boundaries. Driving two piezoelectric actuators at two different locations with sinusoidal signals of 90° phase difference, the propagating waves can be generated on a one-dimensional structure. However, the correlation between the actuators and propagating waves is still not clear. In this paper, we adopt shadow Moire technique to monitor the full-field out-of-plane deformation response of the generated propagating waves in the one-dimensional (1-D) plate with 180 mm in length. A 200-μm-pitch grating was used in this moire interferometry setup. The moire fringe images were captured by a high dynamic camera sequentially. Moire fringes were analyzed by regions of interested (ROI) capturing technique and Fourier transform to retrieve phase information, which included 1-D plate deformation. After the phase was unwrapped and filtered, the instantaneous surface profile was reconstructed. Our experimental results demonstrated that our system can capture propagating waves generated by using the second (60.025 Hz) and the third (109.500 Hz) resonant modes.

Steganography is the method of providing Computer security in which hiding the required information is done by inserting messages within other messages, which is a string of characters containing the useful information, in a carrier image. Using this technique, the required information from the secret image is embedded into individual rows as well as columns present in the pixels of carrier image. In this paper, a novel fuzzy logic based technique is proposed to hide the secret message in individual rows and in individual columns of pixels of the carrier image and to extract the hidden message in the same carrier image. The fuzzification process transforms the image in to various bitplanes. Pixel number and Correlation Value is computed in the original image for hiding the secret information in to the original image. The pixel number and Correlation value is also used as the key for retrieving the embedded image from the receiver side. Pixel merging is done in the sender side by assigning a steganographic value of white and black pixels in original image based on the fuzzy rules by comparing the pixels present in the original and secret images. The information which is hided can be retrieved by using the same fuzzy rules. Experimental results show that the proposed method can hide and retrieve the secret and important messages in an image more effectively and accurately.

Prediction of pleural invasion in lung cancer is crucial in planning appropriate operating procedures and can be assessed using dynamic chest radiography (DCR). However, this assessment is negatively affected by rib shadows in conventional images. The purpose of this study was to develop a deep learning-based bone suppression technique for DCR in various projection directions. Twenty breathing XCAT phantoms with lung tumors and a pair of phantoms consisting only of bone structures were generated. The XCAT phantoms were virtually projected from six directions, resulting in 54000 multidirectional chest X-ray images and were used for training a pix2pix model to estimate bone images from original images. Bone suppression (BS) images were created by subtracting the bone images from the original images and then evaluated based on the peak signal to noise ratio (PSNR), structural similarity index measure (SSIM), and Fréchet Video Distance (FVD). Clinical cases were processed using the trained model as well. Furthermore, lung tumors on the original and BS images were tracked using OpenCV template matching, and the tracking accuracy was compared. The PSNR, SSIM, and FVD were 0.9966, 52.20 and 136.9, respectively. In the visual evaluation, we confirmed the effect of BS without temporal fluctuation of pixel values in both the resulting images of the XCAT phantom and real patients. Furthermore, precise tracking of the targeted tumor was achieved on the resulting BS images even in oblique directions, without any interruption from the rib shadows. These results indicate that our proposed method can effectively reduce bone shadows as well as temporal variations in the effect of bone suppression.

Hyperspectral images (HSI) have high spectral and low spatial resolutions. However, multispectral images (MSI) usually have low spectral and high spatial resolutions. In various applications HSI with high spectral and spatial resolutions are required. In this paper, a new method for spatial resolution enhancement of HSI using high resolution MSI based on sparse coding and linear spectral unmixing (SCLSU) is introduced. In the proposed method (SCLSU), high spectral resolution features of HSI and high spatial resolution features of MSI are fused. In this case, the sparse representation of some high resolution MSI and linear spectral unmixing (LSU) model of HSI and MSI is simultaneously used in order to construct high resolution HSI (HRHSI). The fusion process of HSI and MSI is formulated as an ill-posed inverse problem. It is solved by the Split Augmented Lagrangian Shrinkage Algorithm (SALSA) and an orthogonal matching pursuit (OMP) algorithm. Finally, the proposed algorithm is applied to the Hyperion and ALI datasets. Compared with the other state-of-the-art algorithms such as Coupled Nonnegative Matrix Factorization (CNMF) and local spectral unmixing, the SCLSU has significantly increased the spatial resolution and in addition the spectral content of HSI is well maintained.

The variation of frequency content of a seismic trace with time carries information about the properties of the subsurface reflectivity sequence. As a result, analysis of the data in terms of the local frequency content can provide a worthwhile addition to the standard procedures that are used in seismic processing and seismostratigraphic interpretation. The theory of quadratic time-frequency (TF) representations, such as the Wigner-Ville distribution (WVD), provides a solid foundation for local frequency analysis of seismic data and seismic attribute extraction. However, because of its quadratic nature, the WVD processes cross terms, which can limit the readability of the decomposition. To overcome this problem, we have used the key idea of the maximum entropy method of Burg, to compute a prediction error operator associated with the power spectrum of a given signal. The operator was then used to extend the kernel of Wigner-Ville of the signal, given by the elements of its covariance matrix. The Fourier transform of the extended kernel provided a high-resolution maximum entropy power spectrum of Wigner-Ville. We found, from the framework of the proposed method, how the common seismic attributes can be extracted as characteristics of the local spectrum. Furthermore, we devised a formula to estimate a robust and stable average instantaneous frequency (AIF) in the time domain. The high resolution achieved in the TF domain has been a key aspect for applying the proposed method to the Gulf of Mexico data set. Mapping of the channels and infill lithology is made possible by analyzing the spectral variation of the AIF cube, and the spectral decomposition based on the proposed method allows reliable information on the probable location and extension of a gas reservoir.