Transported into the Bosom of the Empire？ Rethinking How Arthur Conan Doyle Persuades His Readers of British Imperialism in ＂The Speckled Band＂

Melanie C. Green and Timothy C. Brock have proposed their transportation-imagery model of narrative persuasion. They argue that a narrative can evoke imagery in readers＇ mind and then transport readers into the narrative world the author has created, in the course of which the author can persuade readers of the beliefs he＇s put into the narrative. This paper employs this model to rethink how Arthur Conan Doyle persuades his readers of British imperialism in his ＂The Speckled Band＂. First, this model considers the vividness of the narrative and readers＇ participatory response as key factors in readers＇ transportation. The narratives of ＂The Speckled Band＂ are picturesque, and Sherlock Holmes＇ inferential process has reinforced readers＇ participatory response. On the other hand, detective fiction usually has the theme of how the detective/law and order beats the criminal/chaos. That is, Doyle persuades his readers that the British Empire will prevail in ＂The Speckled Band＂ when Holmes, representing the British imperialism, solves the case and kills Dr. Roylott, who represents the evil and savagery in the British colony. According to Green and Brock＇s model, it simply means that there are two narratives （i.e., one is about how the law of the British Empire is challenged, and the other is about how the British Empire＇s stability is restored）, and two complementary transportations before Doyle can successfully persuades his readers. However, if we closely read ＂＇The Speckled Band＂, we can learn that Holmes, who should have represented British law, is guilty of trespassing or taking the law into his own hands. In other words, the complementarity of the two transportations is compromised. Thus, we can conclude that it is highly questionable whether or not Doyle can transport his readers into the bosom of the British Empire.

Non-invasive estimation of the powder size distribution from a single speckle image

Non-invasive characterization of powders may take one of two approaches:imaging and counting individual particles;or relying on scattered light to estimate the particle size distribution(PSD)of the ensemble.The former approach runs into practical difficulties,as the system must conform to the working distance and other restrictions of the imaging optics.The latter approach requires an inverse map from the speckle autocorrelation to the particle sizes.The principle relies on the pupil function determining the basic sidelobe shape,whereas the particle size spread modulates the sidelobe intensity.We recently showed that it is feasible to invert the speckle autocorrelation and obtain the PSD using a neural network,trained efficiently through a physics-informed semi-generative approach.In this work,we eliminate one of the most time-consuming steps of our previous method by engineering the pupil function.By judiciously blocking portions of the pupil,we sacrifice some photons but in return we achieve much enhanced sidelobes and,hence,higher sensitivity to the change of the size distribution.The result is a 60×reduction in total acquisition and processing time,or 0.25 seconds per frame in our implementation.Almost real-time operation in our system is not only more appealing toward rapid industrial adoption,it also paves the way for quantitative characterization of complex spatial or temporal dynamics in drying,blending,and other chemical and pharmaceutical manufacturing processes.

Mechanical behavior of 2G NPR bolt anchored rock samples under static disturbance loading

The deep mining of coal resources is accompanied by severe environmental challenges and various potential engineering hazards.The implementation of NPR(negative Poisson's ratio)bolts are capable of controlling large deformations in the surrounding rock effectively.This paper focuses on studying the mechanical properties of the NPR bolt under static disturbance load.The deep nonlinear mechanical experimental system was used to study the mechanical behavior of rock samples with different anchored types(unanchored/PR anchored/2G NPR anchored)under static disturbance load.The whole process of rock samples was taken by high-speed camera to obtain the real-time failure characteristics under static disturbance load.At the same time,the acoustic emission signal was collected to obtain the key characteristic parameters of acoustic emission such as acoustic emission count,energy,and frequency.The deformation at the failure of the samples was calculated and analyzed by digital speckle software.The findings indicate that the failure mode of rock is influenced by different types of anchoring.The peak failure strength of 2G NPR bolt anchored rock samples exhibits an increase of 6.5%when compared to the unanchored rock samples.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 62.16%and 62.90%,respectively.The maximum deformation of bearing capacity exhibits an increase of 59.27%,while the failure time demonstrates a delay of 42.86%.The peak failure strength of the 2G NPR bolt anchored ones under static disturbance load exhibits an increase of 5.94%when compared to the rock anchored by PR(Poisson's ratio)bolt.The cumulative count and cumulative energy of acoustic emission exhibit a decrease of 47.16%and 43.86%,respectively.The maximum deformation of the bearing capacity exhibits an increase of 50.43%,and the failure time demonstrates a delay of 32%.After anchoring by 2G NPR bolt,anchoring support effectively reduces the risk of damage caused by static disturbance load.These results demonstrate that the support effect of 2G NPR bolt materials surpasses that of PR bolt.

Laser speckle contrast imaging to predict the effect of temporary spinal cord stimulation in postherpetic neuralgia patients: A prospective observational study

Temporary spinal cord stimulation(tSCS)can effectively reduce the pain and severity of postherpetic neuralgia(PHN).However,there are no effective and objective methods for predicting the effects of tSCS on PHN.Laser speckle contrast imaging(LSCI)is frequently used in neurology to evaluate the effectiveness of treatment.To assess the accuracy of LSCI in predicting the impact of tSCS on PHN,14 adult patients receiving tSCS treatments for spinal nerve-innervated(C6-T2)PHN participated in this observational study.Visual analog scale(VAS)assessments and LSCI bloodflow images of the-ngers were recorded after the tSCS procedure.The results showed that the VAS scores of all patients decreased signi-cantly.Moreover,the bloodflow index(BFI)values were signi-cantly higher than they were before the procedure.Increased bloodflow and pain alleviation were positively correlated.The-ndings indicated that spinal nerve PHN(C6-T2)was signi-cantly reduced by tSCS.Pain alleviation by tSCS was positively correlated with increased bloodflow in the hand.The effect of tSCS on PHN may thus be predicted using an independent and consistent indicator such as LSCI.

Subclinical impairment of left ventricular myocardium function in type 2 diabetes mellitus patients with or without hypertension

BACKGROUND Cardiovascular disease has been the leading cause of morbidity and mortality for type 2 diabetes mellitus(T2DM)patients over the last decade.AIM To determine whether layer-specific global longitudinal strain(GLS)combined with peak strain dispersion(PSD)can be used to assess left ventricle(LV)myocardium systolic dysfunction in T2DM patients or without hypertension(HP).METHODS We enrolled 97 T2DM patients,70 T2DM+HP patients and 101 healthy subjects.Layer-specific GLS and PSD were calculated by EchoPAC software in apical three-,four-and two-chamber views.GLS of the epimyocardial,middle-layer and endomyocardial(GLSepi,GLSmid,and GLSendo)were measured and recorded.Receiver operating characteristic analysis was performed to detect LV myocardium systolic dysfunction in T2DM patients.RESULTS There were significant differences in GLSepi,GLSmid,GLSendo,and PSD between healthy subjects,T2DM patients and T2DM patients with HP(P<0.001).Trend tests yielded the ranking of healthy subjects>T2DM patients>T2DM with HP patients in the absolute values of GLSepi,GLSmid and GLSendo(P<0.001),while PSD was ranked healthy subjects<T2DM<T2DM with HP(P<0.001).Layer-specific GLS and PSD had high diagnostic efficiency for detecting LV myocardium systolic dysfunction in T2DM patients,however,the area under the curve(AUC)for layer-specific GLS and PSD combined was significantly higher than the AUCs for the individual indices(P<0.05).CONCLUSION Layer-specific GLS and PSD were associated with LV myocardium systolic dysfunction in T2DM patients,T2DM patients with HP.T2DM patients with HP have more severe LV myocardium systolic dysfunction than T2DM patients without HP and normal control patients.The combination of layer-specific GLS and PSD may provide additional prognostic information for T2DM patients with or without HP.

Evaluation of left ventricular systolic function in type 2 diabetes mellitus patients with and without peripheral vascular disease

BACKGROUND Peripheral vascular disease(PVD)is a common complication of type 2 diabetes mellitus(T2DM).Patients with T2DM have twice the risk of PVD as nondiabetic patients.AIM To evaluate left ventricular(LV)systolic function by layer-specific global longitudinal strain(GLS)and peak strain dispersion(PSD)in T2DM patients with and without PVD.METHODS Sixty-five T2DM patients without PVD,57 T2DM patients with PVD and 63 normal controls were enrolled in the study.Layer-specific GLS[GLS of the epimyocardium(GLSepi),GLS of the middle myocardium(GLSmid)and GLS of the endocardium(GLSendo)]and PSD were calculated.Receiver operating characteristic(ROC)analysis was performed to calculate the sensitivity and specificity of LV systolic dysfunction in T2DM patients with PVD.We calculated Pearson’s correlation coefficients between biochemical data,echocardiographic characteristics,and layer-specific GLS and PSD.RESULTS There were significant differences in GLSepi,GLSmid and GLSendo between normal controls,T2DM patients without PVD and T2DM patients with PVD(P<0.001).Trend tests revealed a ranking of normal controls>T2DM patients without PVD>T2DM patients with PVD in the absolute value of GLS(P<0.001).PSD differed significantly between the three groups,and the trend ranking was as follows:normal controls<T2DM patients without PVD<T2DM patients with PVD(P<0.001).ROC analysis revealed that the combination of layer-specific GLS and PSD had high diagnostic efficiency for detecting LV systolic dysfunction in T2DM patients with PVD.Lowdensity lipoprotein cholesterol was positively correlated with GLSepi,GLSmid and PSD(P<0.05),while LV ejection fraction was negatively correlated with GLSepi,GLSmid and GLSendo in T2DM patients with PVD(P<0.01).CONCLUSION PVD may aggravate the deterioration of LV systolic dysfunction in T2DM patients.Layer-specific GLS and PSD can be used to detect LV systolic dysfunction accurately and conveniently in T2DM patients with or without PVD.

Application of three-dimensional speckle tracking technique in measuring left ventricular myocardial function in patients with diabetes

BACKGROUND Diabetic cardiomyopathy is considered as a chronic complication of diabetes mellitus(DM).Therefore,early detection of left ventricular systolic function(LVSF)damage in DM is essential.AIM To explore the use of the three-dimensional speckle tracking technique(3D-STI)for measuring LVSF in DM patients via meta-analysis.METHODS The electronic databases were retrieved from the initial accessible time to 29 April 2023.The current study involved 9 studies,including 970 subjects.We carried out this meta-analysis to estimate myocardial function in DM compared with controls according to myocardial strain attained by 3D-STI.RESULTS Night articles including 970 subjects were included.No significant difference was detected in the left ventricular ejection fraction between the control and the diabetic group(P>0.05),while differences in global longitudinal strain,global circumferential strain,global radial strain,and global area strain were markedly different between the controls and DM patients(all P<0.05).CONCLUSION The 3D-STI could be applied to accurately measure early LVSF damage in patients with DM.

Advances in the Research Application of Ultrasound Non-Invasive Stress-Strain Loop Technology in Cardiovascular Diseases

The ultrasound pressure-strain loop (PSL) technique is a non-invasive method of examining myocardial work, which takes into account the effect of cardiac afterload on deformation and combines the overall longitudinal strain force of the left ventricle with the changes in the left ventricular pressure, allowing earlier detection of possible subclinical cardiac damage in patients, and a more accurate and non-invasive assessment of the patient’s myocardial work performance. In this article, we will discuss the progress of PSL applications in cardiovascular diseases.

Full-color and less-speckled modified Gerchberg–Saxton algorithm computer-generated hologram floating in a dual-parabolic projection system

This Letter proposes to apply full-color computer-generated holograms to the virtual image projection system so that the viewers can comfortably view floating images. Regarding the spatial division and distribution operation,a modified Gerchberg–Saxton algorithm is used for acquiring the phase infographics, which are input into the spatial light modulator for the reconstructed projection. Such a virtual image projection system could reach the vertical angle of view of 15°–75° and the horizontal angle of view 360°, and the mixed-light modulating proportion contains a 3 m W red light laser, a 2 m W green light laser, and a 2.6 m W blue light laser to achieve the full-color mixed-light proportion with a speckle contrast of 6.65%. The relative diffraction efficiency and root mean square error of the reconstructed image are 95.3% and 0.0524, respectively.

Speckle structured illumination endoscopy with enhanced resolution at wide field of view and depth of field

Structured illumination microscopy(SIM)is one of the most widely applied wide field super resolution imaging techniques with high temporal resolution and low phototoxicity.The spatial resolution of SIM is typically limited to two times of the diffraction limit and the depth of field is small.In this work,we propose and experimentally demonstrate a low cost,easy to implement,novel technique called speckle structured illumination endoscopy(SSIE)to enhance the resolution of a wide field endoscope with large depth of field.Here,speckle patterns are used to excite objects on the sample which is then followed by a blind-SIM algorithm for super resolution image reconstruction.Our approach is insensitive to the 3D morphology of the specimen,or the deformation of illuminations used.It greatly simplifies the experimental setup as there are no calibration protocols and no stringent control of illumination patterns nor focusing optics.We demonstrate that the SSIE can enhance the resolution 2–4.5 times that of a standard white light endoscopic(WLE)system.The SSIE presents a unique route to super resolution in endoscopic imaging at wide field of view and depth of field,which might be beneficial to the practice of clinical endoscopy.

Failure characteristics and the damage evolution of a composite bearing structure in pillar-side cemented paste backfilling

A backfilling body-coal pillar-backfilling body(BPB)structure formed by pillar-side cemented paste backfilling can bear overburden stress and ensure safe mining.However,the failure response of BPB composite samples must be investigated.This paper examines the deformation characteristics and damage evolution of six types of BPB composite samples using a digital speckle correlation method under uniaxial compression conditions.A new damage evolution equation was established on the basis of the input strain energy and dissipated strain energy at the peak stress.The prevention and control mechanisms of the backfilling body on the coal pillar instability were discussed.The results show that the deformation localization and macroscopic cracks of the BPB composite samples first appeared at the coal-backfilling interface,and then expanded to the backfilling elements,ultimately appearing in the coal elements.The elastic strain energy in the BPB composite samples reached a maximum at the peak stress,whereas the dissipated energy continued to accumulate and increase.The damage evolution curve and equation agree well with the test results,providing further understanding of instability prevention and the control mechanisms of the BPB composite samples.The restraining effect on the coal pillar was gradually reduced with decreasing backfilling body element's volume ratio,and the BPB composite structure became more vulnerable to failure.This research is expected to guide the design,stability monitoring,instability prevention,and control of BPB structures in pillar-side cemented paste backfilling mining.

High performance“non-local”generic face reconstruction model using the lightweight Speckle-Transformer(SpT)UNet

Significant progress has been made in computational imaging(CI),in which deep convolutional neural networks(CNNs)have demonstrated that sparse speckle patterns can be reconstructed.However,due to the limited“local”kernel size of the convolutional operator,for the spatially dense patterns,such as the generic face images,the performance of CNNs is limited.Here,we propose a“non-local”model,termed the Speckle-Transformer(SpT)UNet,for speckle feature extraction of generic face images.It is worth noting that the lightweight SpT UNet reveals a high efficiency and strong comparative performance with Pearson Correlation Coefficient(PCC),and structural similarity measure(SSIM)exceeding 0.989,and 0.950,respectively.

Proposed Framework for Detection of Breast Tumors

Computer vision is one of the significant trends in computer science.It plays as a vital role in many applications,especially in the medical field.Early detection and segmentation of different tumors is a big challenge in the medical world.The proposed framework uses ultrasound images from Kaggle,applying five diverse models to denoise the images,using the best possible noise-free image as input to the U-Net model for segmentation of the tumor,and then using the Convolution Neural Network(CNN)model to classify whether the tumor is benign,malignant,or normal.The main challenge faced by the framework in the segmentation is the speckle noise.It’s is a multiplicative and negative issue in breast ultrasound imaging,because of this noise,the image resolution and contrast become reduced,which affects the diagnostic value of this imaging modality.As result,speckle noise reduction is very vital for the segmentation process.The framework uses five models such as Generative Adversarial Denoising Network(DGAN-Net),Denoising U-Shaped Net(D-U-NET),Batch Renormalization U-Net(Br-UNET),Generative Adversarial Network(GAN),and Nonlocal Neutrosophic ofWiener Filtering(NLNWF)for reducing the speckle noise from the breast ultrasound images then choose the best image according to peak signal to noise ratio(PSNR)for each level of speckle-noise.The five used methods have been compared with classical filters such as Bilateral,Frost,Kuan,and Lee and they proved their efficiency according to PSNR in different levels of noise.The five diverse models are achieved PSNR results for speckle noise at level(0.1,0.25,0.5,0.75),(33.354,29.415,27.218,24.115),(31.424,28.353,27.246,24.244),(32.243,28.42,27.744,24.893),(31.234,28.212,26.983,23.234)and(33.013,29.491,28.556,25.011)forDGAN,Br-U-NET,D-U-NET,GANand NLNWF respectively.According to the value of PSNR and level of speckle noise,the best image passed for segmentation using U-Net and classification usingCNNto detect tumor type.The experiments proved the quality ofU-Net and CNN in segmentation and classification respectively,since they achieved 95.11 and 95.13 in segmentation and 95.55 and 95.67 in classification as dice score and accuracy respectively.

A deformation measurement method based on surface texture information of rocks and its application

Users of the digital image correlation method are faced with the problem of poor operability,low repeatability,and lack of standardized specifications for spraying speckles.To solve the problem,the research proposed a rock deformation measurement method that obviates the need to spray speckles.A local binary model was established by using the local binary pattern(LBP)operator based on deep texture features on rock surfaces.The resulting LBP digital speckle pattern can substitute artificial speckle patterns and demonstrates high quality and strong applicability.Based on the LBP digital speckle pattern,the target tracking algorithm was employed to achieve non-contact measurement of the dynamic displacements of rocks.The feasibility and effectiveness of the algorithm in practical application were verified by conducting shear tests on granite and siltstone.Test results show that the deformation characteristics in the displacement nephograms are in line with the measured data pertaining to rock fracturing and conform to the basic characteristics of the shear failure of rocks.The deformation measurement method based on surface texture information can realize non-contact displacement measurement of rocks under conditions without speckles:this obviates the influence of the quality of sprayed speckles on the accuracy of the measurement of deformation.

Novel Framework of Segmentation 3D MRI of Brain Tumors

Medical image segmentation is a crucial process for computer-aided diagnosis and surgery.Medical image segmentation refers to portioning the images into small,disjointed parts for simplifying the processes of analysis and examination.Rician and speckle noise are different types of noise in magnetic resonance imaging(MRI)that affect the accuracy of the segmentation process negatively.Therefore,image enhancement has a significant role in MRI segmentation.This paper proposes a novel framework that uses 3D MRI images from Kaggle and applies different diverse models to remove Rician and speckle noise using the best possible noise-free image.The proposed techniques consider the values of Peak Signal to Noise Ratio(PSNR)and the level of noise as inputs to the attention-U-Net model for segmentation of the tumor.The framework has been divided into three stages:removing speckle and Rician noise,the segmentation stage,and the feature extraction stage.The framework presents solutions for each problem at a different stage of the segmentation.In the first stage,the framework uses Vibrational Mode Decomposition(VMD)along with Block-matching and 3D filtering(Bm3D)algorithms to remove the Rician.Afterwards,the most significant Rician noise-free images are passed to the three different methods:Deep Residual Network(DeRNet),Dilated Convolution Auto-encoder Denoising Network(Di-Conv-AE-Net),andDenoising Generative Adversarial Network(DGAN-Net)for removing the speckle noise.VMDand Bm3D have achieved PSNR values for levels of noise(0,0.25,0.5,0.75)for reducing the Rician noise by(35.243,32.135,28.214,24.124)and(36.11,31.212,26.215,24.123)respectively.The framework also achieved PSNR values for removing the speckle noise process for each level as follows:(34.146,30.313,28.125,24.001),(33.112,29.103,27.110,24.194),and(32.113,28.017,26.193,23.121)forDeRNet,Di-Conv-AE-Net,and DGAN-Net,respectively.The experiments that have been conducted have proved the efficiency of the proposed framework against classical filters such as Bilateral,Frost,Kuan,and Lee according to different levels of noise.The attention gate U-Net achieved 94.66 and 95.03 in the segmentation of free noise images in dice and accuracy,respectively.

Transmissive multifocal laser speckle contrast imaging through thick tissue

Laser speckle contrast imaging(LSCI)is a powerful tool for monitoring blood flow changes in tissue or vessels in vivo,but its applications are limited by shallow penetration depth under reflective imaging configuration.The traditional LSCI setup has been used in transmissive imaging for depth extension up to 2l_(t)–3l_(t)(l_(t)is the transport mean free path),but the blood flow estimation is biased due to the depth uncertainty in large depth of field(DOF)images.In this study,we propose a transmissive multifocal LSCI for depth-resolved blood flow in thick tissue,further extending the transmissive LSCI for tissue thickness up to 12lt.The limited-DOF imaging system is applied to the multifocal acquisition,and the depth of the vessel is estimated using a robust visibility parameter V_(r)in the coherent domain.The accuracy and linearity of depth estimation are tested by Monte Carlo simulations.Based on the proposed method,the model of contrast analysis resolving the depth information is established and verified in a phantom experiment.We demonstrated its effectiveness in acquiring depth-resolved vessel structures and flow dynamics in in vivo imaging of chick embryos.

Generation of high intensity speckles in overlapping laser beams

A new mechanism for the generation of high intensity speckles by coupling of overlapping beams is discovered and studied in detail.Using three-dimensional simulations,the coupling of overlapping beams smoothed by phase plates and by polarization smoothing are investigated in the regime relevant to inertial confinement fusion studies.It is found that the intensity distribution of the laser beam spot can be changed by nonuniform spatial phase modulation,and the speckles formed by the phase plate can be split into smaller speckles with higher intensities,which is favorable for the generation of laser plasma instabilities.Stimulated Brillouin scattering is compared in simulations with and without coupling of the overlapping incident beams,and the results confirm the enhancement of stimulated Brillouin scattering due to this mechanism.

A New Hybrid Model for Segmentation of the Skin Lesion Based on Residual Attention U-Net

Skin segmentation participates significantly in various biomedical applications,such as skin cancer identification and skin lesion detection.This paper presents a novel framework for segmenting the skin.The framework contains two main stages:The first stage is for removing different types of noises from the dermoscopic images,such as hair,speckle,and impulse noise,and the second stage is for segmentation of the dermoscopic images using an attention residual U-shaped Network(U-Net).The framework uses variational Autoencoders(VAEs)for removing the hair noises,the Generative Adversarial Denoising Network(DGAN-Net),the Denoising U-shaped U-Net(D-U-NET),and Batch Renormalization U-Net(Br-U-NET)for remov-ing the speckle noise,and the Laplacian Vector Median Filter(MLVMF)for removing the impulse noise.In the second main stage,the residual attention u-net was used for segmentation.The framework achieves(35.11,31.26,27.01,and 26.16),(36.34,33.23,31.32,and 28.65),and(36.33,32.21,28.54,and 27.11)for removing hair,speckle,and impulse noise,respectively,based on Peak Signal Noise Ratio(PSNR)at the level of(0.1,0.25,0.5,and 0.75)of noise.The framework also achieves an accuracy of nearly 94.26 in the dice score in the process of segmentation before removing noise and 95.22 after removing different types of noise.The experiments have shown the efficiency of the used model in removing noise according to the structural similarity index measure(SSIM)and PSNR and in the segmentation process as well.

A speckle noise suppression method based on surface waves investigation and monitoring data

The internal energy distribution of waves can be described using ocean-wave spectra.In many ways,obtaining wave spectra on a global scale is critical.Surface waves investigation and monitoring onboard the Chinese-French oceanography satellite is the first space-borne instrument for detecting wave spectra specially,which was launched on October 29,2018.It can avoid the shortage of synthetic aperture radar detection results while still having some problems,especially with the effects of speckle noise.In this study,a method to suppress the speckle noise is proposed.First,the empirical formula for background speckle noise is established.Second,many spatio-temporal representative fluctuation spectra are classified and averaged.Third,rational transfer function filtering is used to obtain speckle noise close to the along-track direction.Finally,a signal-to-noise ratio threshold is used to suppress the abnormal speckle noise.This method solves the problems existing in previous denoising methods,such as excessive denoising in the along-track direction and the inability of some abnormal noises to be denoised in the two-dimensional directional wave spectra.

PAN-DeSpeck:A Lightweight Pyramid and Attention-Based Network for SAR Image Despeckling

SAR images commonly suffer fromspeckle noise,posing a significant challenge in their analysis and interpretation.Existing convolutional neural network(CNN)based despeckling methods have shown great performance in removing speckle noise.However,these CNN-basedmethods have a fewlimitations.They do not decouple complex background information in amulti-resolutionmanner.Moreover,they have deep network structures thatmay result in many parameters,limiting their applicability tomobile devices.Furthermore,extracting key speckle information in the presence of complex background is also a major problem with SAR.The proposed study addresses these limitations by introducing a lightweight pyramid and attention-based despeckling(PAN-Despeck)network.The primary objective is to enhance image quality and enable improved information interpretation,particularly on mobile devices and scenarios involving complex backgrounds.The PAN-Despeck network leverages domainspecific knowledge and integrates Gaussian Laplacian image pyramid decomposition for multi-resolution image analysis.By utilizing this approach,complex background information can be effectively decoupled,leading to enhanced despeckling performance.Furthermore,the attention mechanism selectively focuses on key speckle features and facilitates complex background removal.The network incorporates recursive and residual blocks to ensure computational efficiency and accelerate training speed,making it lightweight while maintaining high performance.Through comprehensive evaluations,it is demonstrated that PAN-Despeck outperforms existing image restoration methods.With an impressive average peak signal-to-noise ratio(PSNR)of 28.355114 and a remarkable structural similarity index(SSIM)of 0.905467,it demonstrates exceptional performance in effectively reducing speckle noise in SAR images.The source code for the PAN-DeSpeck network is available on GitHub.