Resource Type

Journal Article 321

Year

2024 1

2023 35

2022 47

2021 41

2020 27

2019 28

2018 20

2017 23

2016 15

2015 5

2014 3

2013 2

2012 7

2011 4

2010 3

2009 4

2008 5

2007 6

2006 12

2005 7

open ︾

Keywords

Multi-agent system 8

Multi-agent systems 6

Deep learning 5

Reinforcement learning 5

Artificial intelligence 3

5G 2

Antenna-in-package (AiP) 2

Compressive sensing 2

Computer vision 2

Consensus 2

Hypervelocity impact 2

Image segmentation 2

Machine learning 2

Multi-model 2

Target tracking 2

X-ray 2

mine hydraulic winder 2

sustainable development 2

2-dimensions optical orthogonal square codes (2D-OOSC) 1

open ︾

Search scope:

排序： Display mode:

Multi-focus image fusion based on fractional-order derivative and intuitionistic fuzzy sets Research Articles

Xue-feng Zhang, Hui Yan, Hao He,zhangxuefeng@mail.neu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.1900737

Abstract: Multi-focus is an increasingly important component in , and it plays a key role in imaging. In this paper, we put forward a novel multi-focus method which employs and . The original image is decomposed into a base layer and a detail layer. Furthermore, a new fractional-order spatial frequency is built to reflect the clarity of the image. The fractional-order spatial frequency is used as a rule for detail layers fusion, and are introduced to fuse base layers. Experimental results demonstrate that the proposed fusion method outperforms the state-of-the-art methods for multi-focus .

Keywords： 像融合；分数阶导数；直觉模糊集；多聚焦图像    

HTML PDF Collect

Dual-constraint burst image denoising method Research Articles

Dan ZHANG, Lei ZHAO, Duanqing XU, Dongming LU,cszhd@zju.edu.cn,cszhl@zju.edu.cn,xdq@zju.edu.cn,ldm@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 2,   Pages 220-233 doi: 10.1631/FITEE.2000353

Abstract: has proven to be an effective mechanism for computer vision tasks, especially for and burst . In this paper, we focus on solving the burst problem and aim to generate a single clean image from a burst of noisy images. We propose to combine the power of block matching and 3D filtering (BM3D) and a convolutional neural network (CNN) for burst . In particular, we design a CNN with a divide-and-conquer strategy. First, we employ BM3D to preprocess the noisy burst images. Then, the preprocessed images and noisy images are fed separately into two parallel CNN branches. The two branches produce somewhat different results. Finally, we use a light CNN block to combine the two outputs. In addition, we improve the performance by optimizing the two branches using two different constraints: a signal constraint and a noise constraint. One maps a clean signal, and the other maps the noise distribution. In addition, we adopt block matching in the network to avoid frame misalignment. Experimental results on synthetic and real noisy images show that our algorithm is competitive with other algorithms.

Keywords： Image denoising     Burst image denoising     Deep learning    

HTML PDF Collect

Amultimodal dense convolution network for blind image quality assessment Research Article

Nandhini CHOCKALINGAM, Brindha MURUGAN

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 11,   Pages 1601-1615 doi: 10.1631/FITEE.2200534

Abstract: Technological advancements continue to expand the communications industry’s potential. Images, which are an important component in strengthening communication, are widely available. Therefore, image quality assessment (IQA) is critical in improving content delivered to end users. Convolutional neural networks (CNNs) used in IQA face two common challenges. One issue is that these methods fail to provide the best representation of the image. The other issue is that the models have a large number of parameters, which easily leads to overfitting. To address these issues, the dense convolution network (DSC-Net), a model with fewer parameters, is proposed for . Moreover, it is obvious that the use of multimodal data for has improved the performance of applications. As a result, fuses the texture features extracted using the gray-level co-occurrence matrix (GLCM) method and spatial features extracted using DSC-Net and predicts the image quality. The performance of the proposed framework on the benchmark synthetic datasets LIVE, TID2013, and KADID-10k demonstrates that the MDSC-Net approach achieves good performance over state-of-the-art methods for the NR-IQA task.

Keywords： No-reference image quality assessment (NR-IQA)     Blind image quality assessment     Multimodal dense convolution network (MDSC-Net)     Deep learning     Visual quality     Perceptual quality    

HTML PDF Collect

Multi-focus image fusion based on fully convolutional networks Research Articles

Rui Guo, Xuan-jing Shen, Xiao-yu Dong, Xiao-li Zhang,zhangxiaoli@jlu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900336

Abstract: We propose a method, in which a fully convolutional network for focus detection (FD-FCN) is constructed. To obtain more precise focus detection maps, we propose to add s in the network to make both detailed and abstract visual information available when using FD-FCN to generate maps. A new training dataset for the proposed network is constructed based on dataset CIFAR-10. The image fusion algorithm using FD-FCN contains three steps: focus maps are obtained using FD-FCN, decision map generation occurs by applying a morphological process on the focus maps, and image fusion occurs using a decision map. We carry out several sets of experiments, and both subjective and objective assessments demonstrate the superiority of the proposed fusion method to state-of-the-art algorithms.

Keywords： 多焦距图像融合；全卷积网络；跳层；性能评估    

HTML PDF Collect

Large Scale Scanning Probe Microscope

Lu Xiaobo,Lu Zuhong,Zhou Qing,Wang Guozhu

Strategic Study of CAE 2004, Volume 6, Issue 9,   Pages 50-55

Abstract:

This paper introduces a type of large scale scanning probe microscope, which adopts the scheme of the separation of large scale scanning from high precise scanning, and the separation of X - Y scanning from vertical detection. The instrument has the advantages such as good repeatability, large scanning scale as well as high resolution. The large scale scanning range is 220 mm × 290 mm × 60 mm and the repeatability is 2～3/μm. The instrument achieves the auto-feeding of the probe, the auto-focusing of the optical microscope and the auto-mosaicking of the scanning image.

Keywords： scanning probe microscope     auto-feeding     auto-focusing     image mosaicking    

HTML PDF Collect

The Application of Two Dimensions Wavelet in Image Edges Detection

Zhang Hongyan,Zhang Dengpan

Strategic Study of CAE 2003, Volume 5, Issue 4,   Pages 61-64

Abstract:

Edges as the main characterization of image vision have been throught as the main content in obtaining image information. Wavelet transform has the capacity for detecting local signal mutation and detects information using multiscale character, so it is taken as the excellent tool to detect the edges of the image information. This paper analyzes the basic theory using two dimensions wavelet to detect image edges on the basis of wavelet transform and then designs the detecting algorithm of the multi-scale edge matching. On the basis of researching results,the application programme is made to analyse the true examples.

Keywords： wavelet transform     multi-scale     edges detection    

HTML PDF Collect

A Focus on Interfaces

Ping Sheng

Engineering 2021, Volume 7, Issue 5,   Pages 552-553 doi: 10.1016/j.eng.2021.02.003

HTML PDF Collect

Image Engineering and Its Research Status in China

Zhang Yujin

Strategic Study of CAE 2000, Volume 2, Issue 8,   Pages 91-94

Abstract:

This paper provides a well-regulated explanation of the definition as well as contents of image engineering, a classification of the theories of image engineering and the applications of image technology. In addition, a comprehensive survey on important Chinese publications about image engineering in the past five years is carried out. An analysis and a discussion of the statistics made on the classification results are also presented. This work shows a general and up-to-date picture of the current status, progress trends and application areas of image engineering in China. It also supplies useful information for readers doing research and/or application works in this field, and provides a helpful reference for editors of journals and potential authors of papers.

Keywords： image engineering     publication     survey    

HTML PDF Collect

A Confocal Endoscope for Cellular Imaging Article

Jiafu Wang,Min Yang,Li Yang,Yun Zhang,Jing Yuan,Qian Liu,Xiaohua Hou,Ling Fu

Engineering 2015, Volume 1, Issue 3,   Pages 351-360 doi: 10.15302/J-ENG-2015081

Abstract:

Since its inception, endoscopy has aimed to establish an immediate diagnosis that is virtually consistent with a histologic diagnosis. In the past decade, confocal laser scanning microscopy has been brought into endoscopy, thus enabling in vivo microscopic tissue visualization with a magnification and resolution comparable to that obtained with the ex vivo microscopy of histological specimens. The major challenge in the development of instrumentation lies in the miniaturization of a fiber-optic probe for microscopic imaging with micron-scale resolution. Here, we present the design and construction of a confocal endoscope based on a fiber bundle with 1.4-μm lateral resolution and 8-frames per second (fps) imaging speed. The fiber-optic probe has a diameter of 2.6 mm that is compatible with the biopsy channel of a conventional endoscope. The prototype of a confocal endoscope has been used to observe epithelial cells of the gastrointestinal tracts of mice and will be further demonstrated in clinical trials. In addition, the confocal endoscope can be used for translational studies of epithelial function in order to monitor how molecules work and how cells interact in their natural environment.

Keywords： cellular resolution     confocal endoscopy     optical biopsy    

HTML PDF Collect

Anovel spiking neural network of receptive field encoding with groups of neurons decision Article

Yong-qiang MA, Zi-ru WANG, Si-yu YU, Ba-dong CHEN, Nan-ning ZHENG, Peng-ju REN

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 1,   Pages 139-150 doi: 10.1631/FITEE.1700714

Abstract: Human information processing depends mainly on billions of neurons which constitute a complex neural network, and the information is transmitted in the form of neural spikes. In this paper, we propose a spiking neural network (SNN), named MD-SNN, with three key features: (1) using receptive field to encode spike trains from images; (2) randomly selecting partial spikes as inputs for each neuron to approach the absolute refractory period of the neuron; (3) using groups of neurons to make decisions. We test MD-SNN on the MNIST data set of handwritten digits, and results demonstrate that: (1) Different sizes of receptive fields influence classification results significantly. (2) Considering the neuronal refractory period in the SNN model, increasing the number of neurons in the learning layer could greatly reduce the training time, effectively reduce the probability of over-fitting, and improve the accuracy by 8.77%. (3) Compared with other SNN methods, MD-SNN achieves a better classification; compared with the convolution neural network, MD-SNN maintains flip and rotation invariance (the accuracy can remain at 90 44% on the test set), and it is more suitable for small sample learning (the accuracy can reach 80 15% for 1000 training samples, which is 7.8 times that of CNN).

Keywords： Tempotron     Receptive field     Difference of Gaussian (DoG)     Flip invariance     Rotation invariance    

HTML PDF Collect

Interactive medical image segmentation with self-adaptive confidence calibration

沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9,   Pages 1332-1348 doi: 10.1631/FITEE.2200299

Abstract: Interactive medical image segmentation based on human-in-the-loop machine learning is a novel paradigm that draws on human expert knowledge to assist medical image segmentation. However, existing methods often fall into what we call interactive misunderstanding, the essence of which is the dilemma in trading off short- and long-term interaction information. To better use the interaction information at various timescales, we propose an interactive segmentation framework, called interactive MEdical image segmentation with self-adaptive Confidence CAlibration (MECCA), which combines action-based confidence learning and multi-agent reinforcement learning. A novel confidence network is learned by predicting the alignment level of the action with short-term interaction information. A confidence-based reward-shaping mechanism is then proposed to explicitly incorporate confidence in the policy gradient calculation, thus directly correcting the model’s interactive misunderstanding. MECCA also enables user-friendly interactions by reducing the interaction intensity and difficulty via label generation and interaction guidance, respectively. Numerical experiments on different segmentation tasks show that MECCA can significantly improve short- and long-term interaction information utilization efficiency with remarkably fewer labeled samples. The demo video is available at https://bit.ly/mecca-demo-video.

Keywords： Medical image segmentation     Interactive segmentation     Multi-agent reinforcement learning     Confidence learning     Semi-supervised learning    

HTML Collect

High-payload completely reversible data hiding in encrypted images by an interpolation technique Article

Di XIAO, Ying WANG, Tao XIANG, Sen BAI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1732-1743 doi: 10.1631/FITEE.1601067

Abstract: We present a new high-payload joint reversible data-hiding scheme for encrypted images. Instead of embedding data in the encrypted image directly, the content owner first uses an interpolation technique to estimate whether the location can be used for embedding and generates a location map before encryption. Next, the data hider embeds the additional data through flipping the most significant bits (MSBs) of the encrypted image according to the location map. At the receiver side, before extracting the additional data and reconstructing the image, the receiver decrypts the image first. Experimental results demonstrate that the proposed method can achieve real reversibility, which means data extraction and image recovery are free of error. Moreover, our scheme can embed more payloads than most existing reversible data hiding schemes in encrypted images.

Keywords： Encrypted image     Data hiding     Image recovery     Real reversibility     Interpolation    

HTML PDF Collect

The Preliminary Study On Malignant Tumors Effects of High Intensive Focused Ultrasound——A Primary Clinical Report On 78 Cases of Malignant Turmors in HIFU Therapy

He Shenxu,Xiong Liulin,Yu Jinsheng,Lan Jiang

Strategic Study of CAE 1999, Volume 1, Issue 2,   Pages 62-66

Abstract:

Aim To evaluate the clinical effect and safety of high intensive focused ultrasound (HIFU). Methods 78 cases malignant tumors in abdomen and pelvis were classified into two groups： hollow organic tumors group such as carcinomas of ractum and bladder etc. and solid organic tumors group such as carcinomas of liver and pancreas etc. were treated by FEP-BY01 pyrotherapier. The clinical effect was evaluated by different criterion according to their group and the safety was evaluated from painness, skin burning, intestine bleeding, perforation and other aspects. Results In 32 cases of hollow organic tumors, CR (Complete Remission) is 65. 6%, PR (Partial Remission) is 34. 4% at discharge. In 46 cases of solid organic tumors, marked effect rate is 15. 6%, effect rate is 80. 4%, and non-effect rate is 4. 3% (because of ribber stopping ultrasound). HIFU combined with a lower dosage radiotherapy and chemotherapy can speed up tumor falling off or atrophy. Conclusions The HIFU is a kind of safe and effective method to treat abdominal malignant tumor, worth being popularized.

Keywords： malignant tumor     pyrotherapy     extracorporeal focused     ultrasound    

HTML PDF Collect

Public key based bidirectional shadow image authentication without pixel expansion in image secret sharing Research Article

Xuehu YAN, Longlong LI, Jia CHEN, Lei SUN,publictiger@126.com

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 1,   Pages 88-103 doi: 10.1631/FITEE.2200118

Abstract: (ISS) is gaining popularity due to the importance of digital images and its wide application to cloud-based distributed storage and multiparty secure computing. generally includes shadow image detection and identification, and plays an important role in ISS. However, traditional dealer-participatory methods, which suffer from significant or storing auxiliary information, authenticate the shadow image mainly during the decoding phase, also known as unidirectional authentication. The authentication of the shadow image in the distributing (encoding) phase is also important for the participant. In this study, we introduce a based bidirectional method in ISS without for a (k,n) threshold. When the dealer distributes each shadow image to a corresponding participant, the participant can authenticate the received shadow image with his/her private key. In the decoding phase, the dealer can authenticate each received shadow image with a secret key; in addition, the dealer can losslessly decode the secret image with any k or more shadow images. The proposed method is validated using theoretical analyses, illustrations, and comparisons.

Keywords： Image secret sharing     Shadow image authentication     Public key     Pixel expansion     Lossless decoding    

HTML PDF Collect

Recent Advances in Passive Digital Image Security Forensics: A Brief Review Review

Xiang Lin, Jian-Hua Li, Shi-Lin Wang, Alan-Wee-Chung Liew, Feng Cheng, Xiao-Sa Huang

Engineering 2018, Volume 4, Issue 1,   Pages 29-39 doi: 10.1016/j.eng.2018.02.008

Abstract:

With the development of sophisticated image editing and manipulation tools, the originality and authenticity of a digital image is usually hard to determine visually. In order to detect digital image forgeries, various kinds of digital image forensics techniques have been proposed in the last decade. Compared with active forensics approaches that require embedding additional information, passive forensics approaches are more popular due to their wider application scenario, and have attracted increasing academic and industrial research interests. Generally speaking, passive digital image forensics detects image forgeries based on the fact that there are certain intrinsic patterns in the original image left during image acquisition or storage, or specific patterns in image forgeries left during the image storage or editing. By analyzing the above patterns, the originality of an image can be authenticated. In this paper, a brief review on passive digital image forensic methods is presented in order to provide a comprehensive introduction on recent advances in this rapidly developing research area. These forensics approaches are divided into three categories based on the various kinds of traces they can be used to track—that is, traces left in image acquisition, traces left in image storage, and traces left in image editing. For each category, the forensics scenario, the underlying rationale, and state-of-the-art methodologies are elaborated. Moreover, the major limitations of the current image forensics approaches are discussed in order to point out some possible research directions or focuses in these areas.

Keywords： Digital image forensics     Image-tampering detection     Multimedia security    

HTML PDF Collect

Title Author Date Type Operation

Multi-focus image fusion based on fractional-order derivative and intuitionistic fuzzy sets

Xue-feng Zhang, Hui Yan, Hao He,zhangxuefeng@mail.neu.edu.cn

Journal Article

Dual-constraint burst image denoising method

Dan ZHANG, Lei ZHAO, Duanqing XU, Dongming LU,cszhd@zju.edu.cn,cszhl@zju.edu.cn,xdq@zju.edu.cn,ldm@zju.edu.cn

Journal Article

Amultimodal dense convolution network for blind image quality assessment

Nandhini CHOCKALINGAM, Brindha MURUGAN

Journal Article

Multi-focus image fusion based on fully convolutional networks

Rui Guo, Xuan-jing Shen, Xiao-yu Dong, Xiao-li Zhang,zhangxiaoli@jlu.edu.cn

Journal Article

Large Scale Scanning Probe Microscope

Lu Xiaobo,Lu Zuhong,Zhou Qing,Wang Guozhu

Journal Article

The Application of Two Dimensions Wavelet in Image Edges Detection

Zhang Hongyan,Zhang Dengpan

Journal Article

A Focus on Interfaces

Ping Sheng

Journal Article

Image Engineering and Its Research Status in China

Zhang Yujin

Journal Article

A Confocal Endoscope for Cellular Imaging

Jiafu Wang,Min Yang,Li Yang,Yun Zhang,Jing Yuan,Qian Liu,Xiaohua Hou,Ling Fu

Journal Article

Anovel spiking neural network of receptive field encoding with groups of neurons decision

Yong-qiang MA, Zi-ru WANG, Si-yu YU, Ba-dong CHEN, Nan-ning ZHENG, Peng-ju REN

Journal Article

Interactive medical image segmentation with self-adaptive confidence calibration

沈楚云,李文浩,徐琪森,胡斌,金博,蔡海滨,朱凤平,李郁欣,王祥丰

Journal Article

High-payload completely reversible data hiding in encrypted images by an interpolation technique

Di XIAO, Ying WANG, Tao XIANG, Sen BAI

Journal Article

The Preliminary Study On Malignant Tumors Effects of High Intensive Focused Ultrasound——A Primary Clinical Report On 78 Cases of Malignant Turmors in HIFU Therapy

He Shenxu,Xiong Liulin,Yu Jinsheng,Lan Jiang

Journal Article

Public key based bidirectional shadow image authentication without pixel expansion in image secret sharing

Xuehu YAN, Longlong LI, Jia CHEN, Lei SUN,publictiger@126.com

Journal Article

Recent Advances in Passive Digital Image Security Forensics: A Brief Review

Xiang Lin, Jian-Hua Li, Shi-Lin Wang, Alan-Wee-Chung Liew, Feng Cheng, Xiao-Sa Huang

Journal Article