Single-pixel imaging(SPI)receives widespread attention due to its superior anti-interference capabilities,and image segmentation technology can effectively facilitate its recognition and information extraction.However...Single-pixel imaging(SPI)receives widespread attention due to its superior anti-interference capabilities,and image segmentation technology can effectively facilitate its recognition and information extraction.However,the complexity of the target scene and plenty of imaging time in SPI make it challenging to achieve high-quality and concise segmentation.In this paper,we investigate the image-free intricate scene semantic segmentation in SPI.Using“learned”illumination patterns allows for the full extraction of the object's spatial information,thereby enabling pixel-level segmentation results through the decoding of the received measurements.Simulation and experimentation show that,in the absence of image reconstruction,the mean intersection over union(MIoU)of segmented image can reach higher than 85%,and the Dice coefficient(DICE)close to 90%even at the sampling ratio of 5%.Our approach may be favorable to applications in medical image segmentation and autonomous driving field.展开更多
Scattering medium in light path will cause distortion of the light field,resulting in poor signal-to-noise ratio(SNR)of ghost imaging.The disturbance is usually eliminated by the method of pre-compensation.We deduce t...Scattering medium in light path will cause distortion of the light field,resulting in poor signal-to-noise ratio(SNR)of ghost imaging.The disturbance is usually eliminated by the method of pre-compensation.We deduce the intensity fluctuation correlation function of the ghost imaging with the disturbance of the scattering medium,which proves that the ghost image consists of two correlated results:the image of scattering medium and the target object.The effect of the scattering medium can be eliminated by subtracting the correlated result between the light field after the scattering medium and the reference light from ghost image,which verifies the theoretical results.Our research may provide a new idea of ghost imaging in harsh environment.展开更多
Forest biodiversity enhances ecosystem functionality and underpins sustainable forest management by improving soil nutrient cycling.As a representative sustainable management practice,tree species mixing(TSM)increases...Forest biodiversity enhances ecosystem functionality and underpins sustainable forest management by improving soil nutrient cycling.As a representative sustainable management practice,tree species mixing(TSM)increases this functionality by regulating plant-soil nutrient interactions.This study compared the effects of TSM management on stand features,plant diversity,and soil microbial properties across different developmental stages of Cunninghamia lanceolataplantations.The results demonstrated that TSM management significantly enhanced the overall functional efficiency of the ecosystem.Specifically,TSM management improved stand features and reduced competition intensity among trees,which increased α-diversity of each vegetation layer while decreasing its β-diversity.Furthermore,TSM management increased litter layer thickness and soil available phosphorus content,with the magnitude of these effects varying across different management stages.Concurrently,although there was a reduction in α-diversity of bacteria(Chao1:−7.3%;Shannon:−2.7%),soil core microbial community exhibited an enrichment of oligotrophic bacteria(Acidibacter:+29.1%)and an increase in core fungal taxa,a shift that enhanced the decomposition of organic matter(litter thickness:+27.8%)and the transformation of nutrients(available nitrogen(N):+32.6%).Structural equation modeling(SEM)further confirmed that TSM management primarily drives soil carbon accumulation through the“tree diversity-core bacterial community-microbial biomass”pathway.In summary,this study reveals that TSM management promotes forest plant diversity and improves litter and soil conditions at the cost of reducing α-diversity and increasing the soil core bacterial community,ultimately leading to enhanced overall ecosystem functional efficiency.This finding provides important guidance for optimizing the structure,function,and resilience of degraded Chinese fir plantations,and offers a scientific basis for future decisions on balancing microbial community changes in the context of species diversity conservation and soil fertility restoration.展开更多
Typical single-pixel imaging techniques for edge detection are mostly based on first-order differential edge detection operators.In this paper,we present a novel edge detection scheme combining Fourier single-pixel im...Typical single-pixel imaging techniques for edge detection are mostly based on first-order differential edge detection operators.In this paper,we present a novel edge detection scheme combining Fourier single-pixel imaging with a second-order Laplacian of Gaussian(LoG)operator.This method utilizes the convolution results of an LoG operator and Fourier basis patterns as the modulated patterns to extract the edge detail of an unknown object without imaging it.The simulation and experimental results demonstrate that our scheme can ensure finer edge detail,especially under a noisy environment,and save half the processing time when compared with a traditional first-order Sobel operator.展开更多
We present an experimental demonstration of ghost imaging of reflective objects with different surface roughness.The influence of the surface roughness, the transverse size of the test detector, and the reflective ang...We present an experimental demonstration of ghost imaging of reflective objects with different surface roughness.The influence of the surface roughness, the transverse size of the test detector, and the reflective angle on the signal-to-noise ratio(SNR) is analyzed by measuring the second-order correlation of the light field based on classical statistical optics. It is shown that the SNR decreases with an increment of the surface roughness and the detector's transverse size or a decrease of the reflective angle. Additionally, the comparative studies between the rough object and the smooth one under the same conditions are also discussed.展开更多
The scattering medium is usually thought to have a negative effect on the imaging process.In this paper,it is shown that the imaging quality of reflective ghost imaging(GI)in the scattering medium can be improved effe...The scattering medium is usually thought to have a negative effect on the imaging process.In this paper,it is shown that the imaging quality of reflective ghost imaging(GI)in the scattering medium can be improved effectively when the binary method is used.By the experimental and the numerical results,it is proved that the existence of the scattering medium is just the cause of this phenomenon,i.e.,the scattering medium has a positive effect on the imaging quality of reflective GI.During this process,the effect from the scattering medium behaves as the random noise which makes the imaging quality of binary ghost imaging have an obvious improvement.展开更多
It is difficult to extract targets under strong environmental disturbance in practice.Ghost imaging(GI)is an innovative antiinterference imaging technology.In this paper,we propose a scheme for target extraction based...It is difficult to extract targets under strong environmental disturbance in practice.Ghost imaging(GI)is an innovative antiinterference imaging technology.In this paper,we propose a scheme for target extraction based on characteristicenhanced pseudo-thermal GI.Unlike traditional GI which relies on training the detected signals or imaging results,our scheme trains the illuminating light fields using a deep learning network to enhance the target’s characteristic response.The simulation and experimental results prove that our imaging scheme is sufficient to perform single-and multiple-target extraction at low measurements.In addition,the effect of a strong scattering environment is discussed,and the results show that the scattering disturbance hardly affects the target extraction effect.The proposed scheme presents the potential application in target extraction through scattering media.展开更多
The array spatial light field is an effective means for improving imaging speed in single-pixel imaging.However,distinguishing the intensity values of each sub-light field in the array spatial light field requires the...The array spatial light field is an effective means for improving imaging speed in single-pixel imaging.However,distinguishing the intensity values of each sub-light field in the array spatial light field requires the help of the array detector or the time-consuming deep-learning algorithm.Aiming at this problem,we propose measurable speckle gradation Hadamard single-pixel imaging(MSG-HSI),which makes most of the refresh mechanism of the device generate the Hadamard speckle patterns and the high sampling rate of the bucket detector and is capable of measuring the light intensity fluctuation of the array spatial light field only by a simple bucket detector.The numerical and experimental results indicate that data acquisition in MSG-HSI is 4 times faster than in traditional Hadamard single-pixel imaging.Moreover,imaging quality in MSG-HSI can be further improved by image stitching technology.Our approach may open a new perspective for single-pixel imaging to improve imaging speed.展开更多
基金Project supported by the Fundamental Research Funds for the Central Universities of China(Grant No.531118010757)。
文摘Single-pixel imaging(SPI)receives widespread attention due to its superior anti-interference capabilities,and image segmentation technology can effectively facilitate its recognition and information extraction.However,the complexity of the target scene and plenty of imaging time in SPI make it challenging to achieve high-quality and concise segmentation.In this paper,we investigate the image-free intricate scene semantic segmentation in SPI.Using“learned”illumination patterns allows for the full extraction of the object's spatial information,thereby enabling pixel-level segmentation results through the decoding of the received measurements.Simulation and experimentation show that,in the absence of image reconstruction,the mean intersection over union(MIoU)of segmented image can reach higher than 85%,and the Dice coefficient(DICE)close to 90%even at the sampling ratio of 5%.Our approach may be favorable to applications in medical image segmentation and autonomous driving field.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.61871431,61971184,and 62001162)。
文摘Scattering medium in light path will cause distortion of the light field,resulting in poor signal-to-noise ratio(SNR)of ghost imaging.The disturbance is usually eliminated by the method of pre-compensation.We deduce the intensity fluctuation correlation function of the ghost imaging with the disturbance of the scattering medium,which proves that the ghost image consists of two correlated results:the image of scattering medium and the target object.The effect of the scattering medium can be eliminated by subtracting the correlated result between the light field after the scattering medium and the reference light from ghost image,which verifies the theoretical results.Our research may provide a new idea of ghost imaging in harsh environment.
基金supported by the National Key Research and Development Program of China(No.2022YFF1303003)the National Natural Science Foundation of China(Nos.32571778,32171510,and 31770449).
文摘Forest biodiversity enhances ecosystem functionality and underpins sustainable forest management by improving soil nutrient cycling.As a representative sustainable management practice,tree species mixing(TSM)increases this functionality by regulating plant-soil nutrient interactions.This study compared the effects of TSM management on stand features,plant diversity,and soil microbial properties across different developmental stages of Cunninghamia lanceolataplantations.The results demonstrated that TSM management significantly enhanced the overall functional efficiency of the ecosystem.Specifically,TSM management improved stand features and reduced competition intensity among trees,which increased α-diversity of each vegetation layer while decreasing its β-diversity.Furthermore,TSM management increased litter layer thickness and soil available phosphorus content,with the magnitude of these effects varying across different management stages.Concurrently,although there was a reduction in α-diversity of bacteria(Chao1:−7.3%;Shannon:−2.7%),soil core microbial community exhibited an enrichment of oligotrophic bacteria(Acidibacter:+29.1%)and an increase in core fungal taxa,a shift that enhanced the decomposition of organic matter(litter thickness:+27.8%)and the transformation of nutrients(available nitrogen(N):+32.6%).Structural equation modeling(SEM)further confirmed that TSM management primarily drives soil carbon accumulation through the“tree diversity-core bacterial community-microbial biomass”pathway.In summary,this study reveals that TSM management promotes forest plant diversity and improves litter and soil conditions at the cost of reducing α-diversity and increasing the soil core bacterial community,ultimately leading to enhanced overall ecosystem functional efficiency.This finding provides important guidance for optimizing the structure,function,and resilience of degraded Chinese fir plantations,and offers a scientific basis for future decisions on balancing microbial community changes in the context of species diversity conservation and soil fertility restoration.
基金supported by the National Natural Science Foundation of China(Nos.61871431,61971184,and 62001162)China Postdoctoral Science Foundation(No.2019M662767)。
文摘Typical single-pixel imaging techniques for edge detection are mostly based on first-order differential edge detection operators.In this paper,we present a novel edge detection scheme combining Fourier single-pixel imaging with a second-order Laplacian of Gaussian(LoG)operator.This method utilizes the convolution results of an LoG operator and Fourier basis patterns as the modulated patterns to extract the edge detail of an unknown object without imaging it.The simulation and experimental results demonstrate that our scheme can ensure finer edge detail,especially under a noisy environment,and save half the processing time when compared with a traditional first-order Sobel operator.
基金National Natural Science Foundation of China(NSFC)(61372102,61571183)Natural Science Foundation of Hunan Province(2017JJ1014)
文摘We present an experimental demonstration of ghost imaging of reflective objects with different surface roughness.The influence of the surface roughness, the transverse size of the test detector, and the reflective angle on the signal-to-noise ratio(SNR) is analyzed by measuring the second-order correlation of the light field based on classical statistical optics. It is shown that the SNR decreases with an increment of the surface roughness and the detector's transverse size or a decrease of the reflective angle. Additionally, the comparative studies between the rough object and the smooth one under the same conditions are also discussed.
基金Natural Science Foundation of Hunan Province(2017JJ1014)National Natural Science Foundation of China(61571183,61871431,61971184)
文摘The scattering medium is usually thought to have a negative effect on the imaging process.In this paper,it is shown that the imaging quality of reflective ghost imaging(GI)in the scattering medium can be improved effectively when the binary method is used.By the experimental and the numerical results,it is proved that the existence of the scattering medium is just the cause of this phenomenon,i.e.,the scattering medium has a positive effect on the imaging quality of reflective GI.During this process,the effect from the scattering medium behaves as the random noise which makes the imaging quality of binary ghost imaging have an obvious improvement.
基金supported by the National Natural Science Foundation of China(Nos.61971184,62001162,62101187)the Hunan Provincial Natural Science Foundation(No.2022JJ40091)the Fundamental Research Funds for the Central Universities(No.531118010757)。
文摘It is difficult to extract targets under strong environmental disturbance in practice.Ghost imaging(GI)is an innovative antiinterference imaging technology.In this paper,we propose a scheme for target extraction based on characteristicenhanced pseudo-thermal GI.Unlike traditional GI which relies on training the detected signals or imaging results,our scheme trains the illuminating light fields using a deep learning network to enhance the target’s characteristic response.The simulation and experimental results prove that our imaging scheme is sufficient to perform single-and multiple-target extraction at low measurements.In addition,the effect of a strong scattering environment is discussed,and the results show that the scattering disturbance hardly affects the target extraction effect.The proposed scheme presents the potential application in target extraction through scattering media.
基金supported by the National Natural Science Foundation of China(Nos.62101187,61971184,and 62001162)the Hunan Provincial Natural Science Foundation(No.2022JJ40091)the Fundamental Research Funds for the Central Universities(No.531118010757)。
文摘The array spatial light field is an effective means for improving imaging speed in single-pixel imaging.However,distinguishing the intensity values of each sub-light field in the array spatial light field requires the help of the array detector or the time-consuming deep-learning algorithm.Aiming at this problem,we propose measurable speckle gradation Hadamard single-pixel imaging(MSG-HSI),which makes most of the refresh mechanism of the device generate the Hadamard speckle patterns and the high sampling rate of the bucket detector and is capable of measuring the light intensity fluctuation of the array spatial light field only by a simple bucket detector.The numerical and experimental results indicate that data acquisition in MSG-HSI is 4 times faster than in traditional Hadamard single-pixel imaging.Moreover,imaging quality in MSG-HSI can be further improved by image stitching technology.Our approach may open a new perspective for single-pixel imaging to improve imaging speed.
