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Adaptive kernel regression and energy concentration criterion for infrared dim small target detection 期刊论文
Optical Engineering, 2021, 卷号: 60, 期号: 12
作者:  M. Ma;  D. Wang;  H. Sun and T. Zhang
收藏  |  浏览/下载：8/0  |  提交时间：2022/06/13
Infrared dim-small target detection based on an improved multiscale fractal feature 期刊论文
Guangxue Jingmi Gongcheng/Optics and Precision Engineering, 2020, 卷号: 28, 期号: 6, 页码: 1375-1386
作者:  Y. Gu,J. Liu,H.-H. Shen,D.-L. Peng and Y. Xu
收藏  |  浏览/下载：2/0  |  提交时间：2021/07/06
Attention-based feature pyramid networks for ship detection of optical remote sensing image 期刊论文
Yaogan Xuebao/Journal of Remote Sensing, 2020, 卷号: 24, 期号: 2, 页码: 107-115
作者:  Y. Yu, H. Ai, X. He, S. Yu, X. Zhong and R. Zhu
收藏  |  浏览/下载：2/0  |  提交时间：2021/07/06
Research on Small-Type and High-Spectral-Resolution Grating Monochromator 期刊论文
Spectroscopy and Spectral Analysis, 2016, 卷号: 36, 期号: 1
作者:  Yang, Z. P.;  Y. G. Tang;  Bayanheshig;  J. C. Cui and J. Yang
收藏  |  浏览/下载：16/0  |  提交时间：2017/09/11
红外与可见光图像融合算法研究 学位论文
博士: 中国科学院大学, 2014
周渝人
收藏  |  浏览/下载：82/0  |  提交时间：2014/08/21
Image compression based on contourlet and no lists SPIHT (EI CONFERENCE) 会议论文
2010 International Conference on Computer, Mechatronics, Control and Electronic Engineering, CMCE 2010, August 24, 2010 - August 26, 2010, Changchun, China
Zhang S.; Xue X.; Shi J.
收藏  |  浏览/下载：38/0  |  提交时间：2013/03/25
The volume of raw image data captured by the high resolution camera is extremely huge. Thus the efficient image compression method should be used to decrease the bit rate. The image compression method based on wavelet is used more widely nowadays. However  two dimensional wavelet is only the tensor product of the one dimensional wavelet whose support region of basis function is extended from interval to square. Contourlet is an image multiscale geometric analysis tool  which could represent image sparsely and has strong capability of nonlinear approximation. The basis function of contourlet is multidirectional and anisotropic. Nevertheless  contourlet is redundant. So the non-redundant Wavelet Based Contourlet Transform (WBCT) is used in this paper. The SPIHT algorithm is very efficient way to coding the significant coefficients. And the improved no lists SPIHT is more easy to implemented by hardware. Image compression method based on the combination of both wavelet based contourlet transform and no lists SPIHT coding is proposed in the paper. Experiment shows that compared to wavelet based scheme the contourlet scheme can reserve the texture of the image. For barbara test image when coding at low bit rate the PSNR can improve about 0.2dB. 2010 IEEE.  
Directional multiscale edge detection using the contourlet transform (EI CONFERENCE) 会议论文
2010 IEEE International Conference on Advanced Computer Control, ICACC 2010, March 27, 2010 - March 29, 2010, 445 Hoes Lane - P.O.Box 1331, Piscataway, NJ 08855-1331, United States
Ma S.-F.; Zheng G.-F.; Jin L.-X.; Han S.-L.; Zhang R.-F.
收藏  |  浏览/下载：24/0  |  提交时间：2013/03/25
Wavelet multiresolution analysis allows us to detect edges at different scales  also to obtain other important aspects of the extracted edges. However  due to the usual two-dimensional tensor product  wavelet transform is not optimal for representing images. The main problem in edge detection using wavelet transform is that it can only capture point-singularities  and the extracted edges are not continuous. In order to solve that problem  we propose a new image edge detection method based on the contourlet transform. The directional multiresolution representation Contourlet takes advantages of the intrinsic geometrical structure of images  and is appropriate for the analysis of the image edges. Using the modulus maxima detection  an image edge detection method based on contourlet transform is proposed. To suppress the image noise effect on edge detection  the scale multiplication in contourlet domain is also proposed. Through real images experiments  the proposed edge detection method's performance for the extracted edges is analyzed and compared with other two edge detection methods. The experiment result proves that the proposed edge detection method improves over wavelet-based techniques and Canny detector  and also works well for noisy images. 2010 IEEE.  
A new approach for the removal of mixed noise based on wavelet transform (EI CONFERENCE) 会议论文
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
Li Y.; Ni H.; Pang W.; Hao Z.
收藏  |  浏览/下载：25/0  |  提交时间：2013/03/25
This paper proposed a new approach for the removal of mixed noise. There are many different ways in image denoising. Donoho et al have proposed a method for image de-noising by thresholding  ambiguity is often resulted in determining the correspondence of a modulus maximum to a singularity. In the light  and indeed  we combine the merits of the two techniques to form a new approach for the removal of mixed noise. At first  the application of their method to image denoising has been extremely successful. But the method of Donoho is based on the assumption that the type of noise is only additive Gaussian noise  we used wavelet singularity detection (WSD) technique to analyze singularities of signal and noise. According to the characteristic that wavelet transform modulus maxima of impulse noise rapidly decreases as the scale increases in wavelet domain  which is not successful for impulse noise. Mallat has also presented a method for signal denoising by discriminating the noise and the signal singularities through an analysis of their wavelet transform modulus maxima (WTMM). Nevertheless  it can be accurately located with multiscale space by going through dyadic orthogonal wavelet transform and removed. Furthermore the Gaussian noise is also removed through a level-dependent thresholding algorithm  the tracing of WTMM is not just tedious procedure computationally  algorithm. The experimental results demonstrate that the proposed method can effectively detect impulse noise and remove almost all of the noise while preserve image details very well.  

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