IET Image Process.最新文献_第5页

An adaptive level set method based on joint estimation dealing with intensity inhomogeneity 基于联合估计的自适应水平集方法处理强度非均匀性

IET Image Process. Pub Date : 2020-12-30 DOI: 10.1049/ipr2.12115

Jiang Zhu, Yan Zeng, Jianqi Li, Shujuan Tian, Haolin Liu

{"title":"An adaptive level set method based on joint estimation dealing with intensity inhomogeneity","authors":"Jiang Zhu, Yan Zeng, Jianqi Li, Shujuan Tian, Haolin Liu","doi":"10.1049/ipr2.12115","DOIUrl":"https://doi.org/10.1049/ipr2.12115","url":null,"abstract":"Automatic object segmentation has been a challenging task due to intensity inhomogeneity. The traditional way is to eliminate the intensity inhomogeneity, which causes the object to lose useful intensity information. The authors propose an adaptive level set method for the segmentation of intensity inhomogeneous images. Firstly, global and local features are utilised to collaboratively estimate the image, which devotes to compensating for intensity inhomogeneity. The local estimation retains detailed spatial information, and the global estimation mainly contains the regional information of the partitioned object. Then, during the construction of the energy functional, joint estimation is introduced to create the external energy. To acquire the precise location of the boundary, a weighting factor indicated by the gradient is introduced into the internal energy. Finally, after the numerical calculation of the energy functional by additive operator splitting algorithm, this method achieves the desired performance in terms of accuracy and robustness. Experimental results verify this method outperforms the comparative methods and can be applied to many real-world sce-narios.","PeriodicalId":13486,"journal":{"name":"IET Image Process.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78649737","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A level-set method for inhomogeneous image segmentation with application to breast thermography images 非均匀图像分割的水平集方法及其在乳腺热成像图像中的应用

IET Image Process. Pub Date : 2020-12-26 DOI: 10.1049/ipr2.12116

Asma Shamsi Koshki, M. Ahmadzadeh, M. Zekri, S. Sadri, E. Mahmoudzadeh

{"title":"A level-set method for inhomogeneous image segmentation with application to breast thermography images","authors":"Asma Shamsi Koshki, M. Ahmadzadeh, M. Zekri, S. Sadri, E. Mahmoudzadeh","doi":"10.1049/ipr2.12116","DOIUrl":"https://doi.org/10.1049/ipr2.12116","url":null,"abstract":"Various level-set methods have been suggested for segmenting images with intensity inhomogeneity as local region-based models. The challenge in these methods is segmenting the inhomogeneous images with smooth edges. These methods cannot properly segment regions with smooth edges in inhomogeneous images. This paper presents a new local region-based active contour model called local self-weighted active contour model. In the proposed method, a novel different weighting technique is applied. In this model, the weight of each neighbour pixel in the energy function is set by a function of its intensity and not its geometrical distance regarding the central pixel as previous methods. Considering this, the presented approach can segment regions with smooth edges in the presence of inhomogeneity as breast thermography images. The experimental results of applying the model on heterogeneous images containing synthetic images and medical images, especially breast thermography images, are compared with well-known local level-set methods which show the perfect capability of the model. The segmentation results were evaluated using the F-score, accuracy, precision and recall criteria. The results show values of 0.8, 0.62, 0.73 and 0.82 for the average accuracy, F-score, precision and recall criteria on the segmentation of breast thermography images, respectively.","PeriodicalId":13486,"journal":{"name":"IET Image Process.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91236276","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Fusion-based simultaneous estimation of reflectance and illumination for low-light image enhancement 基于融合的低光图像反射率和照度同时估计

IET Image Process. Pub Date : 2020-12-24 DOI: 10.1049/ipr2.12114

A. Parihar, Kavinder Singh, Hrithik Rohilla, G. Asnani

引用次数: 17

A new recognition algorithm for high-voltage lines based on improved LSD and convolutional neural networks 基于改进LSD和卷积神经网络的高压线路识别新算法

IET Image Process. Pub Date : 2020-12-07 DOI: 10.1049/ipr2.12031

Yanhong Luo, Xue Yu, Dongsheng Yang

{"title":"A new recognition algorithm for high-voltage lines based on improved LSD and convolutional neural networks","authors":"Yanhong Luo, Xue Yu, Dongsheng Yang","doi":"10.1049/ipr2.12031","DOIUrl":"https://doi.org/10.1049/ipr2.12031","url":null,"abstract":"With the development of high-voltage transmission and artiﬁcial intelligence technology, unmanned line inspection has become the inevitable trend of current electric power inspection. A new recognition algorithm for high-voltage lines is proposed based on colour (Red, Green, Blue) RGB image to support the unmanned line inspection. Firstly, in order to solve the problem of missing weak edges in image edge detection, an improved Canny algorithm is proposed. Fourier transform Gaussian ﬁlter is introduced to enhance the high-frequency signal of the image, which makes the extracted edge information more complete. At the same time, an improved line segment detector (LSD) algorithm is developed to extract the high-voltage line. The complementary edge information of the three channels of the colour RGB image is analyzed, and the calculation formula of the horizontal line angle is improved, which greatly reduces the possibility of false detection and missed detection in the high-voltage line extraction. In addition, the convolution neural network (CNN) is used to accurately recognize the extracted high-voltage lines, which reduces the interference of non–high-voltage lines. Simulation results show that the proposed algorithm has high","PeriodicalId":13486,"journal":{"name":"IET Image Process.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-12-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77410191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Automatic Production of Synthetic Labeled OCT Images Using Active Shape Model 利用主动形状模型自动生成合成标记OCT图像

IET Image Process. Pub Date : 2020-09-08 DOI: 10.1101/2020.09.05.20181917

H. Danesh, K. Maghooli, R. Kafieh, A. Dehghani

引用次数: 2

Efficient and robust segmentation and correction model for medical images 高效鲁棒的医学图像分割与校正模型

IET Image Process. Pub Date : 2018-10-17 DOI: 10.1049/IET-IPR.2018.5164

Yunyun Yang, W. Jia

{"title":"Efficient and robust segmentation and correction model for medical images","authors":"Yunyun Yang, W. Jia","doi":"10.1049/IET-IPR.2018.5164","DOIUrl":"https://doi.org/10.1049/IET-IPR.2018.5164","url":null,"abstract":"Accurate segmentation of medical images plays a very important role in clinical diagnosis so that the segmentation technology for medical images attracts more and more attention. However, most medical images usually suffer from severe intensity inhomogeneity and make accurate segmentation difficult. In this study, the authors propose an efficient and robust active contour model for simultaneous image segmentation and correction. The proposed model not only can accurately segment images with severe intensity inhomogeneity and serious noise but also can eliminate the intensity varying information to get the homogeneous correction images. They first present the level set formulation of the two-phase model, which is then extended to the multi-phase formulation. The split Bregman method is applied to efficiently minimise the proposed energy functionals. The proposed model is tested with lots of synthetic images and medical images with promising results. Experimental results demonstrate that the proposed model can accurately segment and correct the inhomogeneous images with serious noise. Quantitative comparison results of the proposed model and other models illustrate the proposed model is more accurate and more efficient. What's more, the proposed model not only is insensitive to the initial contour, but also is robust to the noise.","PeriodicalId":13486,"journal":{"name":"IET Image Process.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85581787","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Adaptive deblocking filter for transform domain Wyner-Ziv video coding 变换域Wyner-Ziv视频编码的自适应块化滤波器

IET Image Process. Pub Date : 2009-12-04 DOI: 10.1049/IET-IPR.2008.0201

R. Martins, Catarina Brites, J. Ascenso, F. Pereira

{"title":"Adaptive deblocking filter for transform domain Wyner-Ziv video coding","authors":"R. Martins, Catarina Brites, J. Ascenso, F. Pereira","doi":"10.1049/IET-IPR.2008.0201","DOIUrl":"https://doi.org/10.1049/IET-IPR.2008.0201","url":null,"abstract":"Wyner-Ziv (WZ) video coding is a particular case of distributed video coding, the recent video coding paradigm based on the Slepian-Wolf and Wyner-Ziv theorems that exploits the source correlation at the decoder and not at the encoder as in predictive video coding. Although many improvements have been done over the last years, the performance of the state-of-the-art WZ video codecs still did not reach the performance of state-of-the-art predictive video codecs, especially for high and complex motion video content. This is also true in terms of subjective image quality mainly because of a considerable amount of blocking artefacts present in the decoded WZ video frames. This paper proposes an adaptive deblocking filter to improve both the subjective and objective qualities of the WZ frames in a transform domain WZ video codec. The proposed filter is an adaptation of the advanced deblocking filter defined in the H.264/AVC (advanced video coding) standard to a WZ video codec. The results obtained confirm the subjective quality improvement and objective quality gains that can go up to 0.63-dB in the overall for sequences with high motion content when large group of pictures are used.","PeriodicalId":13486,"journal":{"name":"IET Image Process.","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2009-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84968513","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Enhanced reconstruction algorithm for unidirectional distributed video coding 单向分布式视频编码的增强重构算法

IET Image Process. Pub Date : 2009-12-04 DOI: 10.1049/IET-IPR.2008.0195

W. Weerakkody, W. Fernando, A. Kondoz

引用次数: 4

Motion vector refinement in a Wyner-Ziv to H.264 transcoder for mobile telephony 移动电话用Wyner-Ziv转H.264转码器的运动矢量细化

IET Image Process. Pub Date : 2009-12-04 DOI: 10.1049/IET-IPR.2008.0202

José Luis Martínez, G. Fernández-Escribano, H. Kalva, P. Cuenca

引用次数: 7

Transform-domain distributed video coding with rate-distortion-based adaptive quantisation 基于率失真自适应量化的变换域分布式视频编码

IET Image Process. Pub Date : 2009-12-04 DOI: 10.1049/IET-IPR.2008.0207

Wei-Jung Chien, Lina Karam

引用次数: 10