SeisResoDiff: Seismic resolution enhancement based on a diffusion model

High resolution of post-stack seismic data assists in better interpretation of subsurface structures as well as high accuracy of impedance inversion. Therefore, geophysicists consistently strive to acquire higher resolution seismic images in petroleum exploration. Although there have been successful applications of conventional signal processing and machine learning for post-stack seismic resolution enhancement,there is limited reference to the seismic applications of the recent emergence and rapid development of generative artificial intelligence. Hence, we propose to apply diffusion models, among the most popular generative models, to enhance seismic resolution. Specifically, we apply the classic diffusion model—denoising diffusion probabilistic model(DDPM), conditioned on the seismic data in low resolution, to reconstruct corresponding high-resolution images. Herein the entire scheme is referred to as SeisResoDiff. To provide a comprehensive and clear understanding of SeisResoDiff, we introduce the basic theories of diffusion models and detail the optimization objective's derivation with the aid of diagrams and algorithms. For implementation, we first propose a practical workflow to acquire abundant training data based on the generated pseudo-wells. Subsequently, we apply the trained model to both synthetic and field datasets, evaluating the results in three aspects: the appearance of seismic sections and slices in the time domain, frequency spectra, and comparisons with the synthetic data using real well-logging data at the well locations. The results demonstrate not only effective seismic resolution enhancement,but also additional denoising by the diffusion model. Experimental comparisons indicate that training the model on noisy data, which are more realistic, outperforms training on clean data. The proposed scheme demonstrates superiority over some conventional methods in high-resolution reconstruction and denoising ability, yielding more competitive results compared to our previous research.

Beyond 200-Gb/s O-band intensity modulation and direct detection optics with joint look-uptable- based predistortion and digital resolution enhancement for low-cost data center interconnects

We propose a joint look-up-table(LUT)-based nonlinear predistortion and digital resolution enhancement scheme to achieve high-speed and low-cost optical interconnects using low-resolution digital-to-analog converters(DACs).The LUT-based predistortion is employed to mitigate the patterndependent effect(PDE)of a semiconductor optical amplifier(SOA),while the digital resolution enhancer(DRE)is utilized to shape the quantization noise,lowering the requirement for the resolution of DAC.We experimentally demonstrate O-band intensity modulation and direct detection(IM/DD)transmission of 124-GBd 4∕6-level pulse-amplitude modulation ePAMT-4∕6 and 112-GBd PAM-8 signals over a 2-km standard single-mode fiber(SSMF)with 3∕3.5∕4-bit DACs.In the case of 40-km SSMF transmission with an SOAbased preamplifier,124-GBd on-off-keying(OOK)/PAM-3/PAM-4 signals are successfully transmitted with 1.5∕2∕3-bit DACs.To the best of our knowledge,we have achieved the highest net data rates of 235.3-Gb∕s PAM-4,289.7-Gb∕s PAM-6,and 294.7 Gb∕s PAM-8 signals over 2-km SSMF,as well as 117.6-Gb∕s OOK,173.8-Gb∕s PAM-3,and−231.8 Gb∕s PAM-4 signals over 40-km SSMF,employing low-resolution DACs.The experimental results reveal that the joint LUT-based predistortion and DRE effectively mitigate the PDE and improve the signal-to-quantization noise ratio by shaping the noise.The proposed scheme can provide a powerful solution for low-cost IM/DD optical interconnects beyond 200 Gb∕s.

Simultaneous denoising and resolution enhancement of seismic data based on elastic convolution dictionary learning

Enhancing seismic resolution is a key component in seismic data processing, which plays a valuable role in raising the prospecting accuracy of oil reservoirs. However, in noisy situations, existing resolution enhancement methods are difficult to yield satisfactory processing outcomes for reservoir characterization. To solve this problem, we develop a new approach for simultaneous denoising and resolution enhancement of seismic data based on convolution dictionary learning. First, an elastic convolution dictionary learning algorithm is presented to efficiently learn a convolution dictionary with stronger representation capability from the noisy data to be processed. Specifically, the algorithm introduces the elastic L1/2 norm as a sparsity constraint and employs a steepest gradient descent strategy to efficiently solve the frequency-domain linear system with substantial computational cost in a half-quadratic splitting framework. Then, based on the learned convolution dictionary, a weighted convolutional sparse representation paradigm is designed to encode the noisy data to acquire an optimal sparse approximation of the effective signal. Subsequently, a high-resolution dictionary with a broadband spectrum is constructed by the proposed parameter scaling strategy and matched filtering technique on the basis of atomic spectrum modeling. Finally, the optimal sparse approximation of the effective signal and the constructed high-resolution dictionary are used for data reconstruction to obtain the seismic signal with high resolution and high signal-to-noise ratio. Synthetic and field dataset examples are executed to check the effectiveness and reliability of the developed method. The results indicate that this method has a more competitive performance in seismic applications compared with the conventional deconvolution and spectral whitening methods.

Visibility and Resolution Enhancement of Fourth-Order Ghost Interference with Thermal Light

A scheme for fourth-order double-slit ghost interference with a pseudo-thermal light source is proposed. It is shown that not only can the visibility be dramatically enhanced compared to the third-order case, but also higher resolution is demonstrated if we scan two of three reference detectors in opposite directions with the same speed, meanwhile another two in identical directions where the speed of one reference detector is twice the other. The results show that the visibility and resolution improvement of the fourth-order ghost interference fringe can be applied to the Nth-order ghost imaging.

Resolution enhancement of digital holographic microscopy via synthetic aperture:a review

Digital holographic microscopy(DHM),which combines digital holography with optical microscopy,is a wide field,minimally invasive quantitative phase microscopy(QPM)approach for measuring the 3D shape or the inner structure of transparent and translucent samples.However,limited by diffraction,the spatial resolution of conventional DHM is relatively low and incompatible with a wide field of view(FOV)owing to the spatial bandwidth product(SBP)limit of the imaging systems.During the past decades,many efforts have been made to enhance the spatial resolution of DHM while preserving a large FOV by trading with unused degrees of freedom.Illumination modulation techniques,such as oblique illumination,structured illumination,and speckle illumination,can enhance the resolution by adding more high-frequency information to the recording system.Resolution enhancement is also achieved by extrapolation of a hologram or by synthesizing a larger hologram by scanning the sample,the camera,or inserting a diffraction grating between the sample and the camera.For on-chip DHM,spatial resolution is achieved using pixel super-resolution techniques.In this paper,we review various resolution enhancement approaches in DHM and discuss the advantages and disadvantages of these approaches.It is our hope that this review will contribute to advancements in DHM and its practical applications in many fields.

Resolution enhancement of optical scanning holography with a spiral modulated point spread function

In optical scanning holography, one pupil produces a spherical wave and another produces a plane wave. They interfere with each other and result in a fringe pattern for scanning a three-dimensional object. The resolution of the hologram reconstruction is affected by the point spread function(PSF) of the optical system. In this paper, we modulate the PSF by a spiral phase plate, which significantly enhances the lateral and depth resolution. We explain the theory for such resolution enhancement and show simulation results to verify the efficacy of the approach.

Resolution-enhanced single-pixel imaging using the Hadamard transform matrix

We propose a single-pixel imaging(SPI)method to achieve a higher-resolution image via the Hadamard transform matrix.Unlike traditional SPI schemes,this new method recovers images by correlating single-pixel signals with synchronized transformed patterns of Hadamard bases that are actually projected onto the digital micromirror device.Each transform pattern is obtained through the inverse Fourier transform of the pattern acquired by Gaussian filtering of each Hadamard basis in the frequency domain.The proposed scheme is based on a typical SPI experimental setup and does not add any hardware complexity,enabling the transformation of Hadamard matrices and image reconstruction through data processing alone.Therefore,this approach could be considered as an alternative option for achieving fast SPI in a diffraction-limited imaging system,without the need for additional hardware.

Untrained neural network enhances the resolution of structured illumination microscopy under strong background and noise levels

Structured illumination microscopy(SIM)has been widely applied in the superresolution imaging of subcellular dynamics in live cells.Higher spatial resolution is expected for the observation of finer structures.However,further increasing spatial resolution in SIM under the condition of strong background and noise levels remains challenging.Here,we report a method to achieve deep resolution enhancement of SIM by combining an untrained neural network with an alternating direction method of multipliers(ADMM)framework,i.e.,ADMM-DRE-SIM.By exploiting the implicit image priors in the neural network and the Hessian prior in the ADMM framework associated with the optical transfer model of SIM,ADMM-DRE-SIM can further realize the spatial frequency extension without the requirement of training datasets.Moreover,an image degradation model containing the convolution with equivalent point spread function of SIM and additional background map is utilized to suppress the strong background while keeping the structure fidelity.Experimental results by imaging tubulins and actins show that ADMM-DRE-SIM can obtain the resolution enhancement by a factor of∼1.6 compared to conventional SIM,evidencing the promising applications of ADMM-DRE-SIM in superresolution biomedical imaging.

Method of Verification for Manufacturing in Sub-Wavelength Design

We describe a post resolution-enhancement-technique verification method for use in manufacturing data flow. The goal of the method is to verify whether designs function as intended,or more precisely, whether the printed images are consistent with the design intent. The process modeling is described for the model-based verifi cation method. The performance of the method is demonstrated by experiment.

Time-resolution enhanced multi-path OTD measurement using an adaptive filter based incoherent OFDR

High accuracy and time resolution optical transfer delay(OTD)measurement is highly desired in many multi-path applications,such as optical true-time-delay-based array systems and distributed optical sensors.However,the time resolution is usually limited by the frequency range of the probe signal in frequency-multiplexed OTD measurement techniques.Here,we proposed a time-resolution enhanced OTD measurement method based on incoherent optical frequency domain reflectometry(I-OFDR),where an adaptive filter is designed to suppress the spectral leakage from other paths to break the resolution limitation.A weighted least square(WLS)cost function is first established,and then an iteration approach is used to minimize the cost function.Finally,the appropriate filter parameter is obtained according to the convergence results.In a proof-of-concept experiment,the time-domain response of two optical links with a length difference of 900 ps is successfully estimated by applying a probe signal with a bandwidth of 400 MHz.The time resolution is improved by 2.78times compared to the theoretical resolution limit of the inverse discrete Fourier transform(iDFT)algorithm.In addition,the OTD measurement error is below±0.8 ps.The proposed algorithm provides a novel way to improve the measurement resolution without applying a probe signal with a large bandwidth,avoiding measurement errors induced by the dispersion effect.

IMAGING AND MTI PROCESSING BASED ON DUAL-FREQUENCIES DUAL-APERTURES SPACEBORNE SAR

Based on dual-frequencies dual-apertures spaceborne SAR （Synthetic Aperture Radar）, a new SAR system with four receiving channels and two operation modes is presented in this paper, SAR imaging and Moving Target Indication （MTI） are studied in this system. High resolution imaging with wide swath is implemented by the Mode Ⅰ, and MTI is completed by the Mode Ⅱ. High azimuth resolution is achieved by the Displaced Phase Center （DPC） multibeam technique. And the Coherent Accumulation （CA） method, which combines dual channels data of different carrier frequency, is used to enhance the range resolution. For the data of different carrier frequency, the two aperture interferometric processing is executed to implement clutter cancellation, respectively. And the couple of clutter suppressed data are employed to implement Dual Carrier Frequency Conjugate Processing （DCFCP）, then both slow and fast moving targets detection can be completed, followed by moving target imaging. The simulation results show the validity of the signal processing method of this new SAR system.

Phase-only hologram generation based on integral imaging and its enhancement in depth resolution

We introduce a phase-only hologram generation method based on an integral imaging, and propose an enhancement method in representable depth interval. The computational integral imaging reconstruction method is modified based on optical flow to obtain depth-slice images for the focused objects only. A phaseonly hologram for＇ multiple plane images is generated using the iterative Fresnel transform algorithm. In addition, a division method in hologram plane is proposed for enhancement in the representable minimum depth interval.

The development of an algorithm to enhance and match the resolution of satellite measurements from AMSR-E

Microwave radiometers have many applications because of their penetration ability. However, two major problems remain that obstruct the development of microwave research. One factor that limits their commercial application is the relatively low resolution of microwave radiometers. The other is the non-uniform spatial resolution for each frequency of the radiometer. The resolution mismatch becomes a critical consideration when observations at two or more frequencies must be combined. In this paper, we have used the Backus-Gilbert method to solve these two problems, while AMSR-E is chosen as the research object. First, we derived the Backus-Gilbert method in detail. The simulated data were then used to decide the optimum parameters in the Backus-Gilbert method. To enhance the resolution, the Backus-Gilbert method has been applied to the AMSR-E data, which covered the Mexico Gulf and the Amazon River. After resolution was enhanced, detailed information was obtained and compared with visible high resolution data. To match the resolution, the AMSR-E data from the Oklahoma Little Washed were used to compute the Microwave Vegetation Index (MVI), which was developed by J. C. Shi. Compared to the original MVIs, the information contained in the MVIs that were processed by the Backus-Gilbert method is more reliable.

Enhancing image resolution of confocal fluorescence microscopy with deep learning

Super-resolution optical imaging is crucial to the study of cellular processes.Current super-resolution fluorescence microscopy is restricted by the need of special fluorophores or sophisticated optical systems,or long acquisition and computational times.In this work,we present a deep-learning-based super-resolution technique of confocal microscopy.We devise a two-channel attention network(TCAN),which takes advantage of both spatial representations and frequency contents to learn a more precise mapping from low-resolution images to high-resolution ones.This scheme is robust against changes in the pixel size and the imaging setup,enabling the optimal model to generalize to different fluorescence microscopy modalities unseen in the training set.Our algorithm is validated on diverse biological structures and dual-color confocal images of actin-microtubules,improving the resolution from~230 nm to~110 nm.Last but not least,we demonstrate live-cell super-resolution imaging by revealing the detailed structures and dynamic instability of microtubules.

Mode division multiplexing reconstructive spectrometer with an all-fiber photonics lantern

This study presents a high-accuracy,all-fber mode division multiplexing(MDM)reconstructive spectrometer(RS).The MDM was achieved by utilizing a custom-designed 3×1 mode-selective photonics lantern to launch distinct spatial modes into the multimode fber(MMF).This facilitated the information transmission by increasing light scattering processes,thereby encoding the optical spectra more comprehensively into speckle patterns.Spectral resolution of 2 pm and the recovery of 2000 spectral channels were accomplished.Compared to methods employing single-mode excitation and two-mode excitation,the three-mode excitation method reduced the recovered error by 88%and 50%respectively.A resolution enhancement approach based on alternating mode modulation was proposed,reaching the MMF limit for the 3 dB bandwidth of the spectral correlation function.The proof-of-concept study can be further extended to encompass diverse programmable mode excitations.It is not only succinct and highly efcient but also well-suited for a variety of high-accuracy,high-resolution spectral measurement scenarios.