中国开放科研知识云: 检索

Crack image detection based on fractional differential and fractal dimension 期刊论文
2019, 卷号: 13, 页码: 79-85
作者: Cao, Ting; Wang, Weixing; Tighe, Susan; Wang, Shenglin

收藏 | 浏览/下载：6/0 | 提交时间：2019/12/20

feature extraction fractals image texture crack detection image enhancement road building civil engineering computing maintenance engineering crack image detection fractal dimension image processing crack detection method fractional differential dimension crack extraction image enhancement algorithm fuzzy crack boundary crack boundary information extraction algorithm pavement maintenance systems texture details

A two-step approach for underwater image enhancement 会议论文
2017 International Conference on Computer Systems, Electronics and Control, ICCSEC 2017
作者: Wei, D.; Chen, W.; Chen, X.

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Computer control systems Luminance Underwater imaging Underwater photography Constrast Edge-preserving filter Global contrasts Image details Local contrast Two-step approach Underwater scenes Visual qualities Image enhancement

Realistic hair modeling from a hybrid orientation field 期刊论文
VISUAL COMPUTER, 2016, 卷号: 32, 页码: 729-738
作者: Bao, Yongtang; Qi, Yue

收藏 | 浏览/下载：4/0 | 提交时间：2019/12/30

Image-based hair modeling Hybrid orientation field Fractional anisotropy Preserving structural details Tracing hair strand

Realistic hair modeling from a hybrid orientation field 会议论文
33rd Conference on Computer Graphics International (CGI), Heraklion, GREECE, 2016-06-01
作者: Bao, Yongtang; Qi, Yue

收藏 | 浏览/下载：4/0 | 提交时间：2019/12/30

Image-based hair modeling Hybrid orientation field Fractional anisotropy Preserving structural details Tracing hair strand

Single image dehazing using the change of detail prior 期刊论文
NEUROCOMPUTING, 2015, 卷号: 156, 页码: 1-11
作者: Li, Jiafeng; Zhang, Hong; Yuan, Ding; Sun, Mingui

收藏 | 浏览/下载：3/0 | 提交时间：2020/01/06

Image restoration Image enhancement Single image dehazing Change of details Multiple scattering

The application of adaptive enhancement algorithm based on gray entropy in mammary gland CR image (EI CONFERENCE) 会议论文
2012 2nd International Conference on Consumer Electronics, Communications and Networks, CECNet 2012, April 21, 2012 - April 23, 2012, Three Gorges, China
Zhang M.-H.; Zhang Y.-Y.

收藏 | 浏览/下载：26/0 | 提交时间：2013/03/25

Mammary gland is composed entirely of soft tissue with approximate density therefore mammary gland CR medicine radiation image presents a low contrast and slight difference changes may be a manifestation of tumor so it is necessary to enhance mammary gland CR image to improve its visual quality in order to meet the demands of doctor's clinical diagnosis. However the general enhancement algorithms over enhance the contrast and noise due to image details lost aiming at the defects a mammary gland CR medicine image adaptive enhancement arithmetic based on image gray entropy is put forward. The arithmetic adapts dizzy image to magnify selected spatial frequency response in order to enhance the edge details of mammary gland CR images. It can adjust weighted factor K according to image gray characteristics namely pixel gray entropy. Experiments results demonstrate that mammary gland CR image enhanced by the algorithm has abundant details and high signal-to-noise ratio moreover CR image enhanced has good visual effect. So the method is effective and fit for enhancing CR medical radiation image edge details. 2012 IEEE.

Application of adaptive enhancement means in head and neck CR image (EI CONFERENCE) 会议论文
2012 3rd International Conference on Information Technology for Manufacturing Systems, ITMS 2012, September 8, 2012 - September 9, 2012, Qingdao, China
Zhang M.-H.; Zhang Y.-Y.

收藏 | 浏览/下载：25/0 | 提交时间：2013/03/25

Digital CR of head and neck overcomes the disadvantage of regular X-ray radiography which can not reveal bone and soft tissue position deficiency in one exposing and reduces the Xray radiation dose. Meanwhile various factors cause the decline of image quality and images must be enhanced in order to meet demands of doctor's clinical diagnosis. The general enhancement algorithms don't consider body's structure differences and density characteristics. A new adaptive CR enhancement algorithm was proposed in this article and head and neck CR images were processed with this method and compared with linear unsharp masking method. The experiment proves that the details of CR image enhanced were abundant and enhanced CR image had good visual effect SNR was high as well as detail variance /background variance (DV/BV) indicating that this algorithm is suitable for head and neck CR medical images. (2012) Trans Tech Publications Switzerland.

The research of digltal CR medicine image adapitive enhancement method (EI CONFERENCE) 会议论文
4th International Conference on Mechanical and Electrical Technology, ICMET 2012, July 24, 2012 - July 26, 2012, Kuala Lumpur, Malaysia
Ming-Hui Z.; Yao-Yu Z.

收藏 | 浏览/下载：54/0 | 提交时间：2013/03/25

Digital CR medicine radiation image is in doctor's favor and has became medicine imaging technology new hot spot because of its high gray contrast powerful computer disposal function little radiation dosage non-film diagnosis different area consultation. But degradation of digital X-ray medical image such as low contrast and blurring during radiographic imaging caused by complexity of body tissue and effects of X-ray scattering and electrical noise etc. can worsen the results of analysis and diagnosis. So it is usually needed that CR medicine image is enhanced to improve its vision quality and easy to doctor's more accurate diagnosis. The general enhancement algorithms over enhancing the contrast and lose image details aiming at the defects an enhancement algorithm for CR image is proposed based on the ratio of deviation to mean of domain. The arithmetic enhance CR image edge details by adjusting factor K based on the ratio of deviation to mean of domain of CR image. Experiment results demonstrate that the algorithm enhances CR image detail and CR image enhanced has good visual effect the adaptive enhancement method is fit for CR medicine image. (2012) Trans Tech Publications Switzerland.

Multi-focus image fusion algorithm based on adaptive PCNN and wavelet transform (EI CONFERENCE) 会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Imaging Detectors and Applications, May 24, 2011 - May 26, 2011, Beijing, China
Wu Z.-G.; Wang M.-J.; Han G.-L.

收藏 | 浏览/下载：34/0 | 提交时间：2013/03/25

Being an efficient method of information fusion image fusion has been used in many fields such as machine vision medical diagnosis military applications and remote sensing.In this paper Pulse Coupled Neural Network (PCNN) is introduced in this research field for its interesting properties in image processing including segmentation target recognition et al. and a novel algorithm based on PCNN and Wavelet Transform for Multi-focus image fusion is proposed. First the two original images are decomposed by wavelet transform. Then based on the PCNN a fusion rule in the Wavelet domain is given. This algorithm uses the wavelet coefficient in each frequency domain as the linking strength so that its value can be chosen adaptively. Wavelet coefficients map to the range of image gray-scale. The output threshold function attenuates to minimum gray over time. Then all pixels of image get the ignition. So the output of PCNN in each iteration time is ignition wavelet coefficients of threshold strength in different time. At this moment the sequences of ignition of wavelet coefficients represent ignition timing of each neuron. The ignition timing of PCNN in each neuron is mapped to corresponding image gray-scale range which is a picture of ignition timing mapping. Then it can judge the targets in the neuron are obvious features or not obvious. The fusion coefficients are decided by the compare-selection operator with the firing time gradient maps and the fusion image is reconstructed by wavelet inverse transform. Furthermore by this algorithm the threshold adjusting constant is estimated by appointed iteration number. Furthermore In order to sufficient reflect order of the firing time the threshold adjusting constant is estimated by appointed iteration number. So after the iteration achieved each of the wavelet coefficient is activated. In order to verify the effectiveness of proposed rules the experiments upon Multi-focus image are done. Moreover comparative results of evaluating fusion quality are listed. The experimental results show that the method can effectively enhance the edge details and improve the spatial resolution of the image. 2011 SPIE.

Image deblurring with adaptive total variation model (EI CONFERENCE) 会议论文
International Conference on Image Processing and Pattern Recognition in Industrial Engineering, August 7, 2010 - August 8, 2010, Xi'an, China
Bai Y.; Ding Y.; Zhang X.; Jia H.; Guo L.

收藏 | 浏览/下载：10/0 | 提交时间：2013/03/25

In this paper the models of blurring and methods of deblurring are introduced. A kind of nonlinear image deblurring approach is discussed which comes from constrained optimization total variation approaches. An adaptive TV model method of image deblurring based on common TV model methods is proposed. The experimental results indicate that the proposed method can protect the details of the blurry image more efficiently and satisfy some deblurring requirements more adaptively. 2010 SPIE.

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