中国科学院机构知识库网格系统: 检索

Noise analysis and filtering for laser active imaging system 会议论文 OAI收割
2013 2nd International Conference on Sensors, Measurement and lntelligent Materials, ICSMIM 2013, November 16, 2013 - November 17, 2013, Guangzhou, China
Tao S.

收藏 | 浏览/下载：18/0 | 提交时间：2015/04/27

The research of multi-frame target recognition based on laser active imaging 会议论文 OAI收割
5th International Symposium on Photoelectronic Detection and Imaging, ISPDI 2013, June 25, 2013 - June 27, 2013, Beijing, China, June 25, 2013 - June 27, 2013
作者: Wang T.-F.; Sun T.; Chen J.

收藏 | 浏览/下载：9/0 | 提交时间：2014/05/15

Design and image restoration research of a cubic-phase-plate system (EI CONFERENCE) 会议论文 OAI收割
5th International Symposium on Advanced Optical Manufacturing and Testing Technologies: Advanced Optical Manufacturing Technologies, April 26, 2010 - April 29, 2010, Dalian, China
作者: Zhang J.; Zhang J.; Zhang J.; Shi G.; Zhang X.

收藏 | 浏览/下载：18/0 | 提交时间：2013/03/25

Wave-front coding technology is a novel jointly optical and digital imaging technology which can greatly extend the depth of focus of optical systems. The image restoration process is an important part of wave-front coding technology. Using wave-front coding makes the modulation transfer function(MTF) values of the optical systems change little over a range of several times the depth of focus which means the system MTF is quite insensitive to defocus and there is no zero in the passband. So we can design a single filter for the restoration of images in different defocus positions. However it's hard to avoid noise during image acquisition and transmission processes. These noises will be amplified in the image restoration especially in the high frequency part when the MTF drop is relatively low. The restoration process significantly reduces the system signal to noise ratio this way. Aimed at the problem of noise amplification a new algorithm was proposed which incorporated wavelet denoising into the iterative steps of Lucy-Richardson algorithm. Better restoration results were obtained through the new algorithm effectively solving the noise amplification problem of original LR algorithm. Two sets of identical triplet imaging systems were designed in one of which the cubic-phase-plate was added. Imaging experiments of the manufactured systems were carried and the images of a traditional system and a wave-front coded system before and after decoding were compared. The results show that the designed wave-front coded system can extend the depth of focus by 40 times compared with the traditional system while maintaining the light flux and the image plane resolution. 2010 Copyright SPIE - The International Society for Optical Engineering.

Remote sensing image restoration using estimated point spread function (EI CONFERENCE) 会议论文 OAI收割
2010 International Conference on Information, Networking and Automation, ICINA 2010, October 17, 2010 - October 19, 2010, Kunming, China
作者: Yang L.; Yang L.

收藏 | 浏览/下载：27/0 | 提交时间：2013/03/25

In order to reduce image blur caused by the degradation phenomenon in the imaging process the acquired images of the space remote sensing camera are restored. First the frequency-domain notch filter is adopted to remove strip noises in the images. Then degradation function which is referred to as the point spread function (PSF) of the imaging system is estimated using the knife-edge method. To improve the accuracy of the estimation the estimated PSF is adjusted with Gaussian fitting. Finally the images are restored by Wiener filtering with the fitted PSF. The restoration results of the remote sensing images show that almost all strip noises are eliminated by the notch filter. After denoising and restoration the variance of the remote sensing image worked with in this paper increases 30.979 and the gray mean gradient increases 3.312. Due to Gaussian fitting the accuracy of the PSF estimation is heightened. Image restoration with the final PSF is benefit to interpreting and analyzing the remote sensing images. After restoration the contrasts of the restored images are increased and the visual effects become clearer. 2010 IEEE.

CR image filter methods research based on wavelet-domain hidden markov models (EI CONFERENCE) 会议论文 OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者: Wang J.-L.; Wang J.-L.; Li D.-Y.; Wang Y.-P.

收藏 | 浏览/下载：14/0 | 提交时间：2013/03/25

In the procedure of computed radiography imaging we should firstly get across the characters of kinds of noises and the relationship between the image signals and noises. Based on the specialties of computed radiography (CR) images and medical image processing we have study the filtering methods for computed radiography images noises. On the base of analyzing computed radiography imaging system in detail the author think that the major two noises are Gaussian white noise and Poisson noise. Then the different relationship of between two kinds of noises and signal were studied completely. By considering both the characteristics of computed radiography images and the statistical features of wavelet transformed images a multiscale image filtering algorithm which based on two-state hidden markov model (HMM) and mixture Gaussian statistical model has been used to decrease the Gaussian white noise in computed images. By using EM (Expectation Maximization) algorithm to estimate noise coefficients in each scale and obtain power spectrum matrix then this carried through the syncretized two Filter that are IIR(infinite impulse response) Wiener Filter and HMM according to scale size and achieve the experiments as well as the comparison with other denoising methods were presented at last.

A new approach for the removal of mixed noise based on wavelet transform (EI CONFERENCE) 会议论文 OAI收割
ICO20: Remote Sensing and Infrared Devices and Systems, August 21, 2005 - August 26, 2005, Changchun, China
作者: Li Y.; Li Y.; Li Y.; Li Y.

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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.

Study of removing striping noise in CCD image (EI CONFERENCE) 会议论文 OAI收割
ICO20: Optical Information Processing, August 21, 2005 - August 26, 2005, Changchun, China
作者: Liu H.; Liu H.; Liu H.

收藏 | 浏览/下载：11/0 | 提交时间：2013/03/25

Striping noise is the common system noise during formation of image using linear array CCD and has the character of periodicity directivity and banding distributing. It can be caused by errors in internal calibration devices or by slight gain/offset differences among the elements that conform the array of detectors. Striping noise covers up useful information in CCD image and brings adverse effect to image interpretation. On the basis of analyzing wavelet decomposed coefficient the regularities of distribution about striping noise in wavelet coefficient is found thereby the method of wavelet threshold selection which is suitable to striping noise distribution is put forward. According to Donoho's method about denoising using wavelet the image including striping noise is processed. Comparing the power spectrum of processed image with the one of original image polluted by striping noise in frequency field we find pulse brought by striping noise is removed and the goal which reserves image details and reduces stripes is achieved.

Image denoising using improved spatially adaptive proportion-shrinking method based on wavelet transform 会议论文 OAI收割
2005
Hao Z. C.; Zhu M.; Zhao J. Y.

收藏 | 浏览/下载：7/0 | 提交时间：2013/03/28