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Rolling bilateral filter-based text image deblurring 期刊论文
The Visual Computer, 2018, 卷号: 0, 页码: 2019-01-14
作者: Yang, Hang; Zhang, Zhongbo; Guan, Yujing

收藏 | 浏览/下载：6/0 | 提交时间：2019/09/17

Image enhancement Bandpass filters Discrete cosine transforms Image texture Iterative methods Nonlinear filtering Optical transfer function

The new approach for infrared target tracking based on the particle filter algorithm (EI CONFERENCE) 会议论文
International Symposium on Photoelectronic Detection and Imaging 2011: Advances in Infrared Imaging and Applications, May 24, 2011 - May 24, 2011, Beijing, China
Sun H.; Han H.-X.

收藏 | 浏览/下载：50/0 | 提交时间：2013/03/25

Target tracking on the complex background in the infrared image sequence is hot research field. It provides the important basis in some fields such as video monitoring precision and video compression human-computer interaction. As a typical algorithms in the target tracking framework based on filtering and data connection the particle filter with non-parameter estimation characteristic have ability to deal with nonlinear and non-Gaussian problems so it were widely used. There are various forms of density in the particle filter algorithm to make it valid when target occlusion occurred or recover tracking back from failure in track procedure but in order to capture the change of the state space it need a certain amount of particles to ensure samples is enough and this number will increase in accompany with dimension and increase exponentially this led to the increased amount of calculation is presented. In this paper particle filter algorithm and the Mean shift will be combined. Aiming at deficiencies of the classic mean shift Tracking algorithm easily trapped into local minima and Unable to get global optimal under the complex background. From these two perspectives that "adaptive multiple information fusion" and "with particle filter framework combining" we expand the classic Mean Shift tracking framework.Based on the previous perspective we proposed an improved Mean Shift infrared target tracking algorithm based on multiple information fusion. In the analysis of the infrared characteristics of target basis Algorithm firstly extracted target gray and edge character and Proposed to guide the above two characteristics by the moving of the target information thus we can get new sports guide grayscale characteristics and motion guide border feature. Then proposes a new adaptive fusion mechanism used these two new information adaptive to integrate into the Mean Shift tracking framework. Finally we designed a kind of automatic target model updating strategy to further improve tracking performance. Experimental results show that this algorithm can compensate shortcoming of the particle filter has too much computation and can effectively overcome the fault that mean shift is easy to fall into local extreme value instead of global maximum value.Last because of the gray and fusion target motion information this approach also inhibit interference from the background ultimately improve the stability and the real-time of the target track. 2011 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).

Adaptive Wiener filtering with Gaussian fitted point spread function in image restoration (EI CONFERENCE) 会议论文
2011 IEEE 2nd International Conference on Software Engineering and Service Science, ICSESS 2011, July 15, 2011 - July 17, 2011, Beijing, China
Yang L.; Zhang X.; Ren J.

收藏 | 浏览/下载：30/0 | 提交时间：2013/03/25

In the imaging process of the space remote sensing camera there was degradation phenomenon in the acquired images. In order to reduce the image blur caused by the degradation the remote sensing images were restored to give prominence to the characteristic objects in the images. First the frequency-domain notch filter was adopted to remove strip noises in the images. Then using the ground characters with the knife-edge shape in the images the point spread function of the imaging system was estimated. In order to improve the accuracy the estimated point spread function was corrected with Gaussian fitting method. Finally the images were restored using the adaptive Wiener filtering with the fitted point spread function. Experimental results of the real remote sensing images showed that almost all strip noises in the images were eliminated. After the denoised images were restored its variance and its gray mean gradient increased also its laplacian gradient increased. Restoration with Gaussian fitted point spread function is beneficial to interpreting and analyzing the remote sensing images. After restoration the blur phenomenon of the images is reduced. The characters are highlighted and the visual effect of the images is clearer. 2011 IEEE.

Research on image restoration of Roll-Swing imaging seeker (EI CONFERENCE) 会议论文
3rd IEEE International Conference on Advanced Computer Control, ICACC 2011, January 18, 2011 - January 20, 2011, Harbin, China
Bai Y.; Zhang H.; Han X.; Wei Q.; Jia H.; Guo L.

收藏 | 浏览/下载：20/0 | 提交时间：2013/03/25

To achieve a correct image receiving for Roll-Swing imaging seeker the mechanism and imaging process is analyzed. The causes of image rotation are discussed. The influence of the frame encoders' precision on imaging de-rotation quality is analyzed. The Roll-Swing imaging seeker is designed for high-speed aerocraft thus the received images are greatly degraded due to atmospheric turbulence. A new method of image restoration is proposed for turbulence-degraded images in this paper. The method is to get point spread function (PSF) based on the estimation of optical transfer function (OTF) according to the optical system design simulation. Finally to obtain the restored image constrained least squares filtering is used with the known PSF. The experiment results indicate that the new restoration method has a favorable effect to satisfy requirement of the automatic target recognition. 2011 IEEE.

Electro-optical imaging system identification using pseudo-random binary pattern (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
Le Y.; Jian W.; Jianzhong Z.; Qiang S.; Jianzhuo L.

收藏 | 浏览/下载：17/0 | 提交时间：2013/03/25

A method using pseudo-random binary pattern is developed for electro-optical imaging system identification. The imaging system is taken as a stable linear time-invariant and causal filter and its transfer function is measured through the pseudo-random binary sequence impulse responses identification. A digital mirror device (DMD) light projector is developed as the target generator and wavelet thresholding is used to denoise the captured image. Pre-filtering spectral estimation algorithm with adaptive parameter selection is also proposed for the identification process overcoming the challenge brought by the size limit derived from the optical isoplantic region. Simulations and experiments are presented to show the effectiveness of the proposed method.0-64. 2010 IEEE.

The corner detector of teeth image based on the improved SUSAN algorithm (EI CONFERENCE) 会议论文
3rd International Conference on BioMedical Engineering and Informatics, BMEI 2010, October 16, 2010 - October 18, 2010, Yantai, China
Li H.; Guo L.; Chen T.; Wang X.; Yang L.

收藏 | 浏览/下载：12/0 | 提交时间：2013/03/25

In order to detect the corners of the teeth image secondly last we detected the corners of the image through the improved SUSAN corner detector algorithm. Through lots of experiments and comparing with other corner detector methods which were acquired by oral cavity endoscope we segmented the image by the threshold based on the gray value of the image this method can detect the corners of the teeth image effectively in this paper which can offer some available parameters for the 3D reconstruction of the teeth. 2010 IEEE. we used the improved SUSAN corner detector algorithm. In this method firstly we removed the noise of the image by the morphology open operation and median filtering

The research of corner detector of teeth image based on the curvature scale space corner algorithm (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
Li H.; Guo L.; Chen T.; Yang L.; Wang X.

收藏 | 浏览/下载：15/0 | 提交时间：2013/03/25

In order to detect the corners of the teeth image secondly thirdly last this method can detects the corners of the teeth image effectively which were acquired by oral cavity endoscope we segmented the image by the threshold based on the gray value of the image we detected the edge of the teeth image by the Canny edge detector we detected the corners by the adaptive threshold curvature scale corner detector. Through lots of experiments and we compare this method to other corner detector methods which offers some available parameters for the 3D reconstruction of the teeth. 2010 IEEE. in this paper we used the CSS algorithm. In this method firstly we removed the noise of the image by the morphology open operation and median filtering

Sort optimization algorithm of median filtering based on FPGA (EI CONFERENCE) 会议论文
2010 International Conference on Machine Vision and Human-Machine Interface, MVHI 2010, April 24, 2010 - April 25, 2010, Kaifeng, China
Lu Y.; Jiang L.; Dai M.; Li S.

收藏 | 浏览/下载：25/0 | 提交时间：2013/03/25

The traditional sorting algorithm of median filtering is optimized according to the hardware structure features of FPGA. FPGA is used to acquire the data parallelly for comparing the data of the same column in the median filtering window. Comparing results shared by adjacent filter window are saved temporarily to match the new round of median filtering by using FPGA internal resources. This method can reduce the comparing times from current 21 down to 13 and improve the algorithm efficiency nearly 40%.The experimental results prove that the optimized algorithm can filter a 1K1K gray-level image in about 20ms which ensure the proposed algorithm can be applied in the real-time image median filtering system. 2010 IEEE.

Driving and image enhancement for CCD sensing image system (EI CONFERENCE) 会议论文
2010 3rd IEEE International Conference on Computer Science and Information Technology, ICCSIT 2010, July 9, 2010 - July 11, 2010, Chengdu, China
Zhang M.; Ren J.

收藏 | 浏览/下载：18/0 | 提交时间：2013/03/25

The paper designs a driving circuit of high sensitive wide dynamic for CCD sensing imaging system which adopts a Dalsa-made high resolution full-frame 33-mega pixels area CCD FTF5066M. Field Programmable Gate Array (FPGA) is used as the main device to accomplish the timing design of the circuits and power driver control of the sensor. By using the Correlated Double Sampling (CDS) technique the video noise is reduced and the SNR of the system is increased. The output rate of the imaging system designed with integrated chip can reach to 1.3 frames per second through bi-channel output. We use the histogram specification to adjust the brightness of the captured image. And then use the median filtering to suppress the noise. The traditional gray mean gradient (GMG) and the objective evaluation method based on Human Visual System (HVS) used to verify the effect of image enhancement. 2010 IEEE.

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

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.

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