An effective nonrigid image registrationmethod is developed based on the optical flow field(OFF)framework for the complex registration of structure images.In our method,a new force is modeled and integrated into the o...An effective nonrigid image registrationmethod is developed based on the optical flow field(OFF)framework for the complex registration of structure images.In our method,a new force is modeled and integrated into the original optical flow equation to jointly drive the motion direction of pixels.At any point in the offset field,in addition to the force generated by the OFF model derived from local gradient information to drive the pixels in the floating image to infiltrate into the reference pixel set,a new“guiding force”derived from the global grayscale overall trend in a given neighborhood system helps the pixels to more properly spread into the corresponding reference pixel set,particularly when the gradient field of the reference image is unstable.In the experiment,a data set containing several images with complex structures was employed to validate the performance of our registration model.The test results show that our method can quickly and efficiently register complex images and is robust to noise in images.展开更多
Objective: Most of the western music consists of a melody and an accompaniment. The melody is referred to as the foreground, with the accompaniment the background. In visual processing, the lateral occipital complex (...Objective: Most of the western music consists of a melody and an accompaniment. The melody is referred to as the foreground, with the accompaniment the background. In visual processing, the lateral occipital complex (LOC) is known to participate in foreground and background segregation. We investigated the role of LOC in music processing with use of positron emission tomography (PET). Method: Musically na?ve subjects listened to unfamiliar novel melodies with (accompaniment condition) and without the accompaniment (melodic condition). Using a PET subtraction technique, we studied changes in regional cerebral blood flow (rCBF) during the accompaniment condition compared to the melodic condition. Results: The accompanyment condition was associated with bilateral increase of rCBF at the lateral and medial surfaces of both occipital lobes, medial parts of fusiform gyri, cingulate gyri, precentral gyri, insular cortices, and cerebellum. During the melodic condition, the activation at the anterior and posterior portions of the temporal lobes, medial surface of the frontal lobes, inferior frontal gyri, orbitofrontal cortices, inferior parietal lobules, and cerebellum was observed. Conclusions: The LOC participates in recognition of melody with accompaniment, a phenomenon that can be regarded as foreground and background segregation in auditory processing. The fusiform cortex which was known to participate in the color recognition might be activated by the recognition of flourish sounds by the accompaniment, compared to melodic condition. It is supposed that the LOC and fusiform cortex play similar functions beyond the difference of sensory modalities.展开更多
基于计算机视觉的航拍绝缘子缺陷检测方法被广泛应用于电力巡检。针对绝缘子缺陷易受背景复杂、目标尺度较小等因素的影响而导致漏检、误检的问题,提出了一种旨在提高绝缘子缺陷检测精度的绝缘子缺陷检测模型YOLO-insulator。首先,引入...基于计算机视觉的航拍绝缘子缺陷检测方法被广泛应用于电力巡检。针对绝缘子缺陷易受背景复杂、目标尺度较小等因素的影响而导致漏检、误检的问题,提出了一种旨在提高绝缘子缺陷检测精度的绝缘子缺陷检测模型YOLO-insulator。首先,引入基于通道混洗的重参数化卷积(reparameterized convolution based on channel shuffle-one-shot aggregation, RCS-OSA)替换传统的二维卷积C2f,以增强网络的特征提取能力;其次,在颈部网络使用RCS-OSA模块替换部分的C2f卷积,同时引入挤压激励网络(squeeze and excitation network,SENet),以增强模型对通道间关系的捕捉和整体特征的表达能力;最后,针对多种缺陷区域小导致难以检测的问题,提出小目标检测层方法,该层包含更多的缺陷细节信息,有利于缺陷的检测。在自制绝缘子数据集上进行实验验证的结果表明,相对于基线YOLOv8n,YOLO-insulator模型在查准率、召回率、平均精度均值上都实现了提升,有效提高了模型的综合性能。展开更多
可逆信息隐藏(reversible data hiding,RDH)失真包括像素失真和结构失真。考虑到人类视觉系统(human visual system,HVS)对图像结构失真的高敏感性,本文提出使用结构相似性指数(structural similarity index measure,SSIM)作为RDH的评...可逆信息隐藏(reversible data hiding,RDH)失真包括像素失真和结构失真。考虑到人类视觉系统(human visual system,HVS)对图像结构失真的高敏感性,本文提出使用结构相似性指数(structural similarity index measure,SSIM)作为RDH的评价指标。首先,通过分析峰值信噪比(peak signal-to-noise ratio,PSNR)与SSIM的理论增益关系,实现对两个指标的动态同步评估。随后,提出一种基于纹理区域优先选择的高SSIM的RDH方法。将载体图像划分为4个独立像素集进行图像预处理,精准找到纹理区域,进而按照背景复杂度由高到低的顺序嵌入信息。实验结果表明,优先在纹理区域中嵌入信息的策略减小了图像结构失真。在相同的嵌入率下,SSIM值及图像视觉质量均得到了提高。展开更多
Often we encounter documents with text printed on complex color background. Readability of textual contents in such documents is very poor due to complexity of the background and mix up of color(s) of foreground text ...Often we encounter documents with text printed on complex color background. Readability of textual contents in such documents is very poor due to complexity of the background and mix up of color(s) of foreground text with colors of background. Automatic segmentation of foreground text in such document images is very much essential for smooth reading of the document contents either by human or by machine. In this paper we propose a novel approach to extract the foreground text in color document images having complex background. The proposed approach is a hybrid approach which combines connected component and texture feature analysis of potential text regions. The proposed approach utilizes Canny edge detector to detect all possible text edge pixels. Connected component analysis is performed on these edge pixels to identify candidate text regions. Because of background complexity it is also possible that a non-text region may be identified as a text region. This problem is overcome by analyzing the texture features of potential text region corresponding to each connected component. An unsupervised local thresholding is devised to perform foreground segmentation in detected text regions. Finally the text regions which are noisy are identified and reprocessed to further enhance the quality of retrieved foreground. The proposed approach can handle document images with varying background of multiple colors and texture;and foreground text in any color, font, size and orientation. Experimental results show that the proposed algorithm detects on an average 97.12% of text regions in the source document. Readability of the extracted foreground text is illustrated through Optical character recognition (OCR) in case the text is in English. The proposed approach is compared with some existing methods of foreground separation in document images. Experimental results show that our approach performs better.展开更多
Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse de...Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.展开更多
基金supported in part by the National Key Research and Development Program of China under Grant no.2020YFB1806403.
文摘An effective nonrigid image registrationmethod is developed based on the optical flow field(OFF)framework for the complex registration of structure images.In our method,a new force is modeled and integrated into the original optical flow equation to jointly drive the motion direction of pixels.At any point in the offset field,in addition to the force generated by the OFF model derived from local gradient information to drive the pixels in the floating image to infiltrate into the reference pixel set,a new“guiding force”derived from the global grayscale overall trend in a given neighborhood system helps the pixels to more properly spread into the corresponding reference pixel set,particularly when the gradient field of the reference image is unstable.In the experiment,a data set containing several images with complex structures was employed to validate the performance of our registration model.The test results show that our method can quickly and efficiently register complex images and is robust to noise in images.
文摘Objective: Most of the western music consists of a melody and an accompaniment. The melody is referred to as the foreground, with the accompaniment the background. In visual processing, the lateral occipital complex (LOC) is known to participate in foreground and background segregation. We investigated the role of LOC in music processing with use of positron emission tomography (PET). Method: Musically na?ve subjects listened to unfamiliar novel melodies with (accompaniment condition) and without the accompaniment (melodic condition). Using a PET subtraction technique, we studied changes in regional cerebral blood flow (rCBF) during the accompaniment condition compared to the melodic condition. Results: The accompanyment condition was associated with bilateral increase of rCBF at the lateral and medial surfaces of both occipital lobes, medial parts of fusiform gyri, cingulate gyri, precentral gyri, insular cortices, and cerebellum. During the melodic condition, the activation at the anterior and posterior portions of the temporal lobes, medial surface of the frontal lobes, inferior frontal gyri, orbitofrontal cortices, inferior parietal lobules, and cerebellum was observed. Conclusions: The LOC participates in recognition of melody with accompaniment, a phenomenon that can be regarded as foreground and background segregation in auditory processing. The fusiform cortex which was known to participate in the color recognition might be activated by the recognition of flourish sounds by the accompaniment, compared to melodic condition. It is supposed that the LOC and fusiform cortex play similar functions beyond the difference of sensory modalities.
文摘基于计算机视觉的航拍绝缘子缺陷检测方法被广泛应用于电力巡检。针对绝缘子缺陷易受背景复杂、目标尺度较小等因素的影响而导致漏检、误检的问题,提出了一种旨在提高绝缘子缺陷检测精度的绝缘子缺陷检测模型YOLO-insulator。首先,引入基于通道混洗的重参数化卷积(reparameterized convolution based on channel shuffle-one-shot aggregation, RCS-OSA)替换传统的二维卷积C2f,以增强网络的特征提取能力;其次,在颈部网络使用RCS-OSA模块替换部分的C2f卷积,同时引入挤压激励网络(squeeze and excitation network,SENet),以增强模型对通道间关系的捕捉和整体特征的表达能力;最后,针对多种缺陷区域小导致难以检测的问题,提出小目标检测层方法,该层包含更多的缺陷细节信息,有利于缺陷的检测。在自制绝缘子数据集上进行实验验证的结果表明,相对于基线YOLOv8n,YOLO-insulator模型在查准率、召回率、平均精度均值上都实现了提升,有效提高了模型的综合性能。
文摘可逆信息隐藏(reversible data hiding,RDH)失真包括像素失真和结构失真。考虑到人类视觉系统(human visual system,HVS)对图像结构失真的高敏感性,本文提出使用结构相似性指数(structural similarity index measure,SSIM)作为RDH的评价指标。首先,通过分析峰值信噪比(peak signal-to-noise ratio,PSNR)与SSIM的理论增益关系,实现对两个指标的动态同步评估。随后,提出一种基于纹理区域优先选择的高SSIM的RDH方法。将载体图像划分为4个独立像素集进行图像预处理,精准找到纹理区域,进而按照背景复杂度由高到低的顺序嵌入信息。实验结果表明,优先在纹理区域中嵌入信息的策略减小了图像结构失真。在相同的嵌入率下,SSIM值及图像视觉质量均得到了提高。
文摘Often we encounter documents with text printed on complex color background. Readability of textual contents in such documents is very poor due to complexity of the background and mix up of color(s) of foreground text with colors of background. Automatic segmentation of foreground text in such document images is very much essential for smooth reading of the document contents either by human or by machine. In this paper we propose a novel approach to extract the foreground text in color document images having complex background. The proposed approach is a hybrid approach which combines connected component and texture feature analysis of potential text regions. The proposed approach utilizes Canny edge detector to detect all possible text edge pixels. Connected component analysis is performed on these edge pixels to identify candidate text regions. Because of background complexity it is also possible that a non-text region may be identified as a text region. This problem is overcome by analyzing the texture features of potential text region corresponding to each connected component. An unsupervised local thresholding is devised to perform foreground segmentation in detected text regions. Finally the text regions which are noisy are identified and reprocessed to further enhance the quality of retrieved foreground. The proposed approach can handle document images with varying background of multiple colors and texture;and foreground text in any color, font, size and orientation. Experimental results show that the proposed algorithm detects on an average 97.12% of text regions in the source document. Readability of the extracted foreground text is illustrated through Optical character recognition (OCR) in case the text is in English. The proposed approach is compared with some existing methods of foreground separation in document images. Experimental results show that our approach performs better.
基金supported by the National Natural Science Foundation of China(Nos.61906168,62202429 and 62272267)the Zhejiang Provincial Natural Science Foundation of China(No.LY23F020023)the Construction of Hubei Provincial Key Laboratory for Intelligent Visual Monitoring of Hydropower Projects(No.2022SDSJ01)。
文摘Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.
