When dehazing underwater images,the patch-by-patch dark channel prior(DCP) method is frequently used.After the DCP-based processing,there are still some drawbacks,such as patch artifacts,and these artifacts will serio...When dehazing underwater images,the patch-by-patch dark channel prior(DCP) method is frequently used.After the DCP-based processing,there are still some drawbacks,such as patch artifacts,and these artifacts will seriously affect the subjective quality of some challenging images.To remove the patch artifacts from the DCP-guided enhancement mechanism,this paper proposes a coordinated underwater dark channel prior(CUDCP) method.The proposed method considers the characteristics of the red-green-blue channels with different attenuation situations,and thus the attenuation ratios of the red-green-blue channels are adaptively coordinated in diverse images.The requirement for color restoration is then assessed by an evaluation criterion,and the color restoration is carried out by using the compensated gray world(CGW) theory,which further coordinates the intensity of various red-green-blue channels.Our method next applies a patch-division average filter in accordance with the sub-patch classification.On the typical dataset,the enhanced images of our CUDCP method have higher average underwater image quality measure(UIQM) scores(about 2.274 8) when compared with the original images and those of some state-of-the-art enhancement methods,while the computational cost of CUDCP(about 88.618 8 s) is slightly higher than that of the original DCP(about 87.493 8 s).The experimental results demonstrate that in comparison to state-of-the-art enhancement methods,the proposed method can significantly reduce patch artifacts in challenging image enhancement,while maintaining the objective quality of such underwater images,and also enhancing their subjective quality at a reasonable computational cost.展开更多
The nonlocal means( NLM) has been widely used in image processing. In this paper,we introduce a modified weight function for NLM denoising, which will compute the nonlocal similarities among the pre-processing pixel p...The nonlocal means( NLM) has been widely used in image processing. In this paper,we introduce a modified weight function for NLM denoising, which will compute the nonlocal similarities among the pre-processing pixel patches instead of the commonly used similarity measure based on noisy observations. By the law of large number,the norm for the pre-processing pixel patches is closer to the norm of the original clean pixel patches,so the proposed weight functions are more optimized and the selected similar patches are more accurate. Experimental results indicate the proposed algorithm achieves better restored results compared to the classical NLM's method.展开更多
Sparse representation has attracted extensive attention and performed well on image super-resolution（SR） in the last decade. However, many current image SR methods face the contradiction of detail recovery and artif...Sparse representation has attracted extensive attention and performed well on image super-resolution（SR） in the last decade. However, many current image SR methods face the contradiction of detail recovery and artifact suppression. We propose a multi-resolution dictionary learning（MRDL） model to solve this contradiction, and give a fast single image SR method based on the MRDL model. To obtain the MRDL model, we first extract multi-scale patches by using our proposed adaptive patch partition method（APPM）. The APPM divides images into patches of different sizes according to their detail richness. Then, the multiresolution dictionary pairs, which contain structural primitives of various resolutions, can be trained from these multi-scale patches.Owing to the MRDL strategy, our SR algorithm not only recovers details well, with less jag and noise, but also significantly improves the computational efficiency. Experimental results validate that our algorithm performs better than other SR methods in evaluation metrics and visual perception.展开更多
A super-resolution reconstruction algorithm is proposed. The algorithm is based on the idea of the sparse representation of signals, by using the fact that the sparsest representation of a sig- nal is unique as the co...A super-resolution reconstruction algorithm is proposed. The algorithm is based on the idea of the sparse representation of signals, by using the fact that the sparsest representation of a sig- nal is unique as the constraint of the patched-based reconstruction, and compensating residual errors of the reconstruction results both locally and globally to solve the distortion problem in patch-based reconstruction algorithms. Three reconstruction algorithms are compared. The results show that the images reconstructed with the new algorithm have the best quality.展开更多
A simple and effective image inpainting method is proposed in this paper, which is proved to be suitable for different kinds of target regions with shapes from little scraps to large unseemly objects in a wide range o...A simple and effective image inpainting method is proposed in this paper, which is proved to be suitable for different kinds of target regions with shapes from little scraps to large unseemly objects in a wide range of images. It is an important improvement upon the traditional image inpainting techniques. By introducing a new bijeetive-mapping term into the matching cost function, the artificial repetition problem in the final inpainting image is practically solved. In addition, by adopting an inpainting error map, not only the target pixels are refined gradually during the inpainting process but also the overlapped target patches are combined more seamlessly than previous method. Finally, the inpainting time is dramatically decreased by using a new acceleration method in the matching process.展开更多
In this paper, a novel Magnetic Resonance (MR) reconstruction framework which combines image-wise and patch-wise sparse prior is proposed. For addressing, a truncated beta-Bernoulli process is firstly employed to enfo...In this paper, a novel Magnetic Resonance (MR) reconstruction framework which combines image-wise and patch-wise sparse prior is proposed. For addressing, a truncated beta-Bernoulli process is firstly employed to enforce sparsity on overlapping image patches emphasizing local structures. Due to its properties, beta-Bernoulli process can adaptive infer the sparsity (number of non-zero coefficients) of each patch, an appropriate dictionary, and the noise variance simultaneously, which are prerequisite for iterative image reconstruction. Secondly, a General Gaussian Distribution (GGD) prior is introduced to engage image-wise sparsity for wavelet coefficients, which can be then estimated by a threshold denoising algorithm. Finally, MR image is reconstructed by patch-wise estimation, image-wise estimation and under-sampled k-space data with least square data fitting. Experimental results have demonstrated that proposed approach exhibits excellent reconstruction performance. Moreover, if the image is full of similar low-dimensional-structures, proposed algorithm has dramatically improved Peak Signal to Noise Ratio (PSNR) 7～9 dB, with comparisons to other state-of-art compressive sampling methods.展开更多
A broadband microstrip patch antenna was analyzed and designed.Full wave analysis method(FWAM) was employed to show that a stacked microstrip dual patch antenna(SMDPA) might have a much wider bandwidth than that of ...A broadband microstrip patch antenna was analyzed and designed.Full wave analysis method(FWAM) was employed to show that a stacked microstrip dual patch antenna(SMDPA) might have a much wider bandwidth than that of the ordinanry uni patch one.By means of discrete complex image theory(DCIT),the Sommerfeld integrals (SI) involved were accurately calculated at a speed several hundred times faster than numerical integration method(NIM).The feeding structure of the SMDPA was then improved and the bandwidth was extended to about 22% or more for voltage standing wave ratio (VSWR)s≤2 Finally,a matching network was constructed to obtain a bandwidth of about 25% for s≤1.5.展开更多
The proximal esophagus is rarely examined,and its inspection is often inadequate.Optical chromoendoscopy techniques such as narrow band imaging improve the detection rate of inlet patches in the proximal esophagus,a r...The proximal esophagus is rarely examined,and its inspection is often inadequate.Optical chromoendoscopy techniques such as narrow band imaging improve the detection rate of inlet patches in the proximal esophagus,a region in which their prevalence is likely underestimated.Various studies have reported correlations between these esophageal marks with different issues such as Barrett’s esophagus,but these findings remain controversial.Conflicting reports complicate the process of interpreting the clinical features of esophageal inlet patches and underestimate their importance.Unfortunately,the limited clinical data and statistical analyses make reaching any conclusions difficult.It is hypothesized that inlet patches are correlated with various esophageal and extraesophageal symptoms,diagnoses and the personalized therapeutic management of patients with inlet patches as well as the differential diagnosis for premalignant lesions or early cancers.Due to its potential underdiagnosis,there are no consensus guidelines for the management and follow up of inlet patches.This review focuses on questions that were raised from published literature on esophageal inlet patches in adults.展开更多
Mangshan pitviper, Protobothrops mangshanensis （formerly Zhaoermia mangshanensis） is endemic to China. Unfortunately, due to the decreasing size of its wild populations, this snake has been listed as critically enda...Mangshan pitviper, Protobothrops mangshanensis （formerly Zhaoermia mangshanensis） is endemic to China. Unfortunately, due to the decreasing size of its wild populations, this snake has been listed as critically endangered. Re- search carried out on the Mangshan pitviper＇s population ecology and captive reproduction has revealed that the unique head patch patterns of different individuals may potentially be used as a noninvasive recognition biometric character. We collected head patch pattern images of 40 individuals of P. mangshanensis between 1994 and 2011. By comparing each pitviper＇s head patch pattern, we found that the head patch pattern of individual snakes was different and unique. Additionally, we observed and recorded the head patch pattern characters of four adults and five juveniles before and af- ter ecdysis. Our findings confirmed that head patch patterns of Mangshan pitvipers are unique and stable, remaining un- changed after ecdysis. Thus, individuals can be quickly identified by examining the head patch pattern within a specific recognition area on the head. This method may be useful for noninvasive individual recognition in many other species that display color patch pattern variations, especially in studies of endangered species where the use of invasive marking techniques is undesirable.展开更多
Due to highly underdetermined nature of Single Image Super-Resolution(SISR)problem,deep learning neural networks are required to be more deeper to solve the problem effectively.One of deep neural networks successful i...Due to highly underdetermined nature of Single Image Super-Resolution(SISR)problem,deep learning neural networks are required to be more deeper to solve the problem effectively.One of deep neural networks successful in the Super-Resolution(SR)problem is ResNet which can render the capability of deeper networks with the help of skip connections.However,zero padding(ZP)scheme in the network restricts benefits of skip connections in SRResNet and its performance as the ratio of the number of pure input data to that of zero padded data increases.In this paper.we consider the ResNet with Partial Convolution based Padding(PCP)instead of ZP to solve SR problem.Since training of deep neural networks using patch images is advantageous in many aspects such as the number of training image data and network complexities,patch image based SR performance is compared with single full image based one.The experimental results show that patch based SRResNet SR results are better than single full image based ones and the performance of deep SRResNet with PCP is better than the one with ZP.展开更多
This paper focuses on the high intensity filaments (dye patches) embedded in dye plumes in a wall-bounded shear flow, to investigate the shear effect on the dye patch distribution. Motivated by the widely concerned in...This paper focuses on the high intensity filaments (dye patches) embedded in dye plumes in a wall-bounded shear flow, to investigate the shear effect on the dye patch distribution. Motivated by the widely concerned inverse estimation of the source location, we try extracting useful information to know the source location from down-stream dye patches. Accordingly, we changed the dye injection location at different distances from the wall and made observations at different downstream (diffusion) distances from the source. The orientation angle and roundness of dye patches were concerned to examine the shear effect and dye patch characteristics. To capture the dye plume images, a planar laser induced fluorescence (PLIF) technique was used. The orientation and roundness of each dye patch were calculated by least-square fitting. The statistics of both the orientation angle and the roundness were compared with those in homogeneous turbulent cases to reveal the shear effect. Different from uniformly-orientated dye patches in the homogeneous flow, larger occurrence probabilities with positive orientation angles of dye patches are observed in wall-bounded shear flow, in particular, when the injection location is near the wall. As with information extraction for the inverse estimation of source location, it is found that the orientation distribution of dye patches is independent of the diffusion distance, but related with the injection location from the wall. While for the homogeneous flow cases, a strong dependence on the diffusion distance is observed in the orientation distribution profiles. As for the roundness, similar aspects are found regarding the dependencies on the injection location in shear flow and on diffusion distance in homogeneous flow.展开更多
基金supported by the Graduate Student Innovation Fund of Donghua University (No.GSIF-DH-M-2022011)the National Natural Science Foundation of China (No.62001099)。
文摘When dehazing underwater images,the patch-by-patch dark channel prior(DCP) method is frequently used.After the DCP-based processing,there are still some drawbacks,such as patch artifacts,and these artifacts will seriously affect the subjective quality of some challenging images.To remove the patch artifacts from the DCP-guided enhancement mechanism,this paper proposes a coordinated underwater dark channel prior(CUDCP) method.The proposed method considers the characteristics of the red-green-blue channels with different attenuation situations,and thus the attenuation ratios of the red-green-blue channels are adaptively coordinated in diverse images.The requirement for color restoration is then assessed by an evaluation criterion,and the color restoration is carried out by using the compensated gray world(CGW) theory,which further coordinates the intensity of various red-green-blue channels.Our method next applies a patch-division average filter in accordance with the sub-patch classification.On the typical dataset,the enhanced images of our CUDCP method have higher average underwater image quality measure(UIQM) scores(about 2.274 8) when compared with the original images and those of some state-of-the-art enhancement methods,while the computational cost of CUDCP(about 88.618 8 s) is slightly higher than that of the original DCP(about 87.493 8 s).The experimental results demonstrate that in comparison to state-of-the-art enhancement methods,the proposed method can significantly reduce patch artifacts in challenging image enhancement,while maintaining the objective quality of such underwater images,and also enhancing their subjective quality at a reasonable computational cost.
基金National Natural Science Foundations of China(Nos.U1504603,61301229)Key Scientific Research Project of Colleges and Universities in Henan Province,China(Nos.18A120002,19A110014)
文摘The nonlocal means( NLM) has been widely used in image processing. In this paper,we introduce a modified weight function for NLM denoising, which will compute the nonlocal similarities among the pre-processing pixel patches instead of the commonly used similarity measure based on noisy observations. By the law of large number,the norm for the pre-processing pixel patches is closer to the norm of the original clean pixel patches,so the proposed weight functions are more optimized and the selected similar patches are more accurate. Experimental results indicate the proposed algorithm achieves better restored results compared to the classical NLM's method.
文摘Sparse representation has attracted extensive attention and performed well on image super-resolution（SR） in the last decade. However, many current image SR methods face the contradiction of detail recovery and artifact suppression. We propose a multi-resolution dictionary learning（MRDL） model to solve this contradiction, and give a fast single image SR method based on the MRDL model. To obtain the MRDL model, we first extract multi-scale patches by using our proposed adaptive patch partition method（APPM）. The APPM divides images into patches of different sizes according to their detail richness. Then, the multiresolution dictionary pairs, which contain structural primitives of various resolutions, can be trained from these multi-scale patches.Owing to the MRDL strategy, our SR algorithm not only recovers details well, with less jag and noise, but also significantly improves the computational efficiency. Experimental results validate that our algorithm performs better than other SR methods in evaluation metrics and visual perception.
基金Supported by the Basic Research Foundation of Beijing Institute of Technology(3050012211105)
文摘A super-resolution reconstruction algorithm is proposed. The algorithm is based on the idea of the sparse representation of signals, by using the fact that the sparsest representation of a sig- nal is unique as the constraint of the patched-based reconstruction, and compensating residual errors of the reconstruction results both locally and globally to solve the distortion problem in patch-based reconstruction algorithms. Three reconstruction algorithms are compared. The results show that the images reconstructed with the new algorithm have the best quality.
基金Supported by the National Natural Science Foundation of China （No. 60403044, No. 60373070） and partly funded by Microsoft Research Asia： Project 2004-Image-01.
文摘A simple and effective image inpainting method is proposed in this paper, which is proved to be suitable for different kinds of target regions with shapes from little scraps to large unseemly objects in a wide range of images. It is an important improvement upon the traditional image inpainting techniques. By introducing a new bijeetive-mapping term into the matching cost function, the artificial repetition problem in the final inpainting image is practically solved. In addition, by adopting an inpainting error map, not only the target pixels are refined gradually during the inpainting process but also the overlapped target patches are combined more seamlessly than previous method. Finally, the inpainting time is dramatically decreased by using a new acceleration method in the matching process.
基金Supported by the National Natural Science Foundation of China (No. 30900328, 61172179)the Fundamental Research Funds for the Central Universities (No.2011121051)the Natural Science Foundation of Fujian Province of China (No. 2012J05160)
文摘In this paper, a novel Magnetic Resonance (MR) reconstruction framework which combines image-wise and patch-wise sparse prior is proposed. For addressing, a truncated beta-Bernoulli process is firstly employed to enforce sparsity on overlapping image patches emphasizing local structures. Due to its properties, beta-Bernoulli process can adaptive infer the sparsity (number of non-zero coefficients) of each patch, an appropriate dictionary, and the noise variance simultaneously, which are prerequisite for iterative image reconstruction. Secondly, a General Gaussian Distribution (GGD) prior is introduced to engage image-wise sparsity for wavelet coefficients, which can be then estimated by a threshold denoising algorithm. Finally, MR image is reconstructed by patch-wise estimation, image-wise estimation and under-sampled k-space data with least square data fitting. Experimental results have demonstrated that proposed approach exhibits excellent reconstruction performance. Moreover, if the image is full of similar low-dimensional-structures, proposed algorithm has dramatically improved Peak Signal to Noise Ratio (PSNR) 7～9 dB, with comparisons to other state-of-art compressive sampling methods.
文摘A broadband microstrip patch antenna was analyzed and designed.Full wave analysis method(FWAM) was employed to show that a stacked microstrip dual patch antenna(SMDPA) might have a much wider bandwidth than that of the ordinanry uni patch one.By means of discrete complex image theory(DCIT),the Sommerfeld integrals (SI) involved were accurately calculated at a speed several hundred times faster than numerical integration method(NIM).The feeding structure of the SMDPA was then improved and the bandwidth was extended to about 22% or more for voltage standing wave ratio (VSWR)s≤2 Finally,a matching network was constructed to obtain a bandwidth of about 25% for s≤1.5.
文摘The proximal esophagus is rarely examined,and its inspection is often inadequate.Optical chromoendoscopy techniques such as narrow band imaging improve the detection rate of inlet patches in the proximal esophagus,a region in which their prevalence is likely underestimated.Various studies have reported correlations between these esophageal marks with different issues such as Barrett’s esophagus,but these findings remain controversial.Conflicting reports complicate the process of interpreting the clinical features of esophageal inlet patches and underestimate their importance.Unfortunately,the limited clinical data and statistical analyses make reaching any conclusions difficult.It is hypothesized that inlet patches are correlated with various esophageal and extraesophageal symptoms,diagnoses and the personalized therapeutic management of patients with inlet patches as well as the differential diagnosis for premalignant lesions or early cancers.Due to its potential underdiagnosis,there are no consensus guidelines for the management and follow up of inlet patches.This review focuses on questions that were raised from published literature on esophageal inlet patches in adults.
基金funded by the National Natural Science Foundation of China (No. 31071946)the Wild Animal Conservation Fund of the State Forestry Administration of China (2011)the Provincial Natural Science Foundation of Hunan, China (No. 09JJ3030)
文摘Mangshan pitviper, Protobothrops mangshanensis （formerly Zhaoermia mangshanensis） is endemic to China. Unfortunately, due to the decreasing size of its wild populations, this snake has been listed as critically endangered. Re- search carried out on the Mangshan pitviper＇s population ecology and captive reproduction has revealed that the unique head patch patterns of different individuals may potentially be used as a noninvasive recognition biometric character. We collected head patch pattern images of 40 individuals of P. mangshanensis between 1994 and 2011. By comparing each pitviper＇s head patch pattern, we found that the head patch pattern of individual snakes was different and unique. Additionally, we observed and recorded the head patch pattern characters of four adults and five juveniles before and af- ter ecdysis. Our findings confirmed that head patch patterns of Mangshan pitvipers are unique and stable, remaining un- changed after ecdysis. Thus, individuals can be quickly identified by examining the head patch pattern within a specific recognition area on the head. This method may be useful for noninvasive individual recognition in many other species that display color patch pattern variations, especially in studies of endangered species where the use of invasive marking techniques is undesirable.
文摘Due to highly underdetermined nature of Single Image Super-Resolution(SISR)problem,deep learning neural networks are required to be more deeper to solve the problem effectively.One of deep neural networks successful in the Super-Resolution(SR)problem is ResNet which can render the capability of deeper networks with the help of skip connections.However,zero padding(ZP)scheme in the network restricts benefits of skip connections in SRResNet and its performance as the ratio of the number of pure input data to that of zero padded data increases.In this paper.we consider the ResNet with Partial Convolution based Padding(PCP)instead of ZP to solve SR problem.Since training of deep neural networks using patch images is advantageous in many aspects such as the number of training image data and network complexities,patch image based SR performance is compared with single full image based one.The experimental results show that patch based SRResNet SR results are better than single full image based ones and the performance of deep SRResNet with PCP is better than the one with ZP.
文摘This paper focuses on the high intensity filaments (dye patches) embedded in dye plumes in a wall-bounded shear flow, to investigate the shear effect on the dye patch distribution. Motivated by the widely concerned inverse estimation of the source location, we try extracting useful information to know the source location from down-stream dye patches. Accordingly, we changed the dye injection location at different distances from the wall and made observations at different downstream (diffusion) distances from the source. The orientation angle and roundness of dye patches were concerned to examine the shear effect and dye patch characteristics. To capture the dye plume images, a planar laser induced fluorescence (PLIF) technique was used. The orientation and roundness of each dye patch were calculated by least-square fitting. The statistics of both the orientation angle and the roundness were compared with those in homogeneous turbulent cases to reveal the shear effect. Different from uniformly-orientated dye patches in the homogeneous flow, larger occurrence probabilities with positive orientation angles of dye patches are observed in wall-bounded shear flow, in particular, when the injection location is near the wall. As with information extraction for the inverse estimation of source location, it is found that the orientation distribution of dye patches is independent of the diffusion distance, but related with the injection location from the wall. While for the homogeneous flow cases, a strong dependence on the diffusion distance is observed in the orientation distribution profiles. As for the roundness, similar aspects are found regarding the dependencies on the injection location in shear flow and on diffusion distance in homogeneous flow.
