A novel feature fusion method is proposed for the edge detection of color images. Except for the typical features used in edge detection, the color contrast similarity and the orientation consistency are also selected...A novel feature fusion method is proposed for the edge detection of color images. Except for the typical features used in edge detection, the color contrast similarity and the orientation consistency are also selected as the features. The four features are combined together as a parameter to detect the edges of color images. Experimental results show that the method can inhibit noisy edges and facilitate the detection for weak edges. It has a better performance than conventional methods in noisy environments.展开更多
To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform ...To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.展开更多
The evolution in communication techniques has created wide threats for crucial information transfer through a communication channel. Covert communication with steganography is a skill of concealing secret information ...The evolution in communication techniques has created wide threats for crucial information transfer through a communication channel. Covert communication with steganography is a skill of concealing secret information within cover object and hence shields the data theft over rapidly growing network.Recently, diverse steganography techniques using edge identification have been proposed in literature.Numerous methods however utilize certain pixels in the cover image for inserting edge information,resulting in significant deformation. The conventional edge detection method limits the deployment of edge detection in steganography as concealing the information would introduce some variations to the cover image. Hence inserting data in pixel areas recognized by existing conventional edge detection techniques like canny cannot ensure the recognition of the exact edge locations for the cover and stego images. In this paper, an Adaptive steganography method based on novel fuzzy edge identification is proposed. The method proposed is proficient of estimating the precise edge areas of a cover image and also ensures the exact edge location after embedding the secret message. Experimental results reveal that the technique has attained good imperceptibility compared to the Hayat AI-Dmour and Ahmed AIAni Edge XOR method in spatial domain.展开更多
针对鱼类目标检测存在精度低和计算量大的问题,提出了一种基于改进YOLOv8模型的轻量化鱼类目标检测方法YOLOv8-FCW。首先,引入FasterNet中的FasterBlock替换YOLOv8中C2f模块的Bottleneck结构,减少网络模型的冗余计算;其次,引入注意力机...针对鱼类目标检测存在精度低和计算量大的问题,提出了一种基于改进YOLOv8模型的轻量化鱼类目标检测方法YOLOv8-FCW。首先,引入FasterNet中的FasterBlock替换YOLOv8中C2f模块的Bottleneck结构,减少网络模型的冗余计算;其次,引入注意力机制CBAM(Convolutional Block Attention Module),实现高效提取鱼体特征,提升网络模型检测精度;最后,引入动态非单调聚焦机制WIoU(Wise Intersection over Union)替代CIoU(Complete Intersection over Union),加快网络模型的收敛速度,提升网络模型的检测性能。结果显示,与原模型相比,改进YOLOv8-FCW模型精确率提升了1.6个百分点,召回率提升了5.1个百分点,平均精确率均值提升了2.4个百分点,权重和计算量分别减少为原模型的80%和79%。该模型具有较高的精确率和较强的鲁棒性,能够帮助养殖者精确计算鱼群数量,提高养殖效率。展开更多
基金supported partly by the National Basic Research Program of China (2005CB724303)the National Natural Science Foundation of China (60671062) Shanghai Leading Academic Discipline Project (B112).
文摘A novel feature fusion method is proposed for the edge detection of color images. Except for the typical features used in edge detection, the color contrast similarity and the orientation consistency are also selected as the features. The four features are combined together as a parameter to detect the edges of color images. Experimental results show that the method can inhibit noisy edges and facilitate the detection for weak edges. It has a better performance than conventional methods in noisy environments.
基金supported by the National Natural Science Foundation of China(6067309760702062)+3 种基金the National HighTechnology Research and Development Program of China(863 Program)(2008AA01Z1252007AA12Z136)the National ResearchFoundation for the Doctoral Program of Higher Education of China(20060701007)the Program for Cheung Kong Scholarsand Innovative Research Team in University(IRT 0645).
文摘To preserve the sharp features and details of the synthetic aperture radar （SAR） image effectively when despeckling, a despeckling algorithm with edge detection in nonsubsampled second generation bandelet transform （NSBT） domain is proposed. First, the Canny operator is utilized to detect and remove edges from the SAR image. Then the NSBT which has an optimal approximation to the edges of images and a hard thresholding rule are used to approximate the details while despeckling the edge-removed image. Finally, the removed edges are added to the reconstructed image. As the edges axe detected and protected, and the NSBT is used, the proposed algorithm reaches the state-of-the-art effect which realizes both despeckling and preserving edges and details simultaneously. Experimental results show that both the subjective visual effect and the mainly objective performance indexes of the proposed algorithm outperform that of both Bayesian wavelet shrinkage with edge detection and Bayesian least square-Gaussian scale mixture （BLS-GSM）.
文摘The evolution in communication techniques has created wide threats for crucial information transfer through a communication channel. Covert communication with steganography is a skill of concealing secret information within cover object and hence shields the data theft over rapidly growing network.Recently, diverse steganography techniques using edge identification have been proposed in literature.Numerous methods however utilize certain pixels in the cover image for inserting edge information,resulting in significant deformation. The conventional edge detection method limits the deployment of edge detection in steganography as concealing the information would introduce some variations to the cover image. Hence inserting data in pixel areas recognized by existing conventional edge detection techniques like canny cannot ensure the recognition of the exact edge locations for the cover and stego images. In this paper, an Adaptive steganography method based on novel fuzzy edge identification is proposed. The method proposed is proficient of estimating the precise edge areas of a cover image and also ensures the exact edge location after embedding the secret message. Experimental results reveal that the technique has attained good imperceptibility compared to the Hayat AI-Dmour and Ahmed AIAni Edge XOR method in spatial domain.
文摘针对鱼类目标检测存在精度低和计算量大的问题,提出了一种基于改进YOLOv8模型的轻量化鱼类目标检测方法YOLOv8-FCW。首先,引入FasterNet中的FasterBlock替换YOLOv8中C2f模块的Bottleneck结构,减少网络模型的冗余计算;其次,引入注意力机制CBAM(Convolutional Block Attention Module),实现高效提取鱼体特征,提升网络模型检测精度;最后,引入动态非单调聚焦机制WIoU(Wise Intersection over Union)替代CIoU(Complete Intersection over Union),加快网络模型的收敛速度,提升网络模型的检测性能。结果显示,与原模型相比,改进YOLOv8-FCW模型精确率提升了1.6个百分点,召回率提升了5.1个百分点,平均精确率均值提升了2.4个百分点,权重和计算量分别减少为原模型的80%和79%。该模型具有较高的精确率和较强的鲁棒性,能够帮助养殖者精确计算鱼群数量,提高养殖效率。
