We present a method for restoring the recordings obtained from surveillance cameras whose quality deteriorates due to dirt or water that gathers on the camera's lens. The method is designed to operate in the surve...
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ISBN:
(纸本)9781479923427
We present a method for restoring the recordings obtained from surveillance cameras whose quality deteriorates due to dirt or water that gathers on the camera's lens. The method is designed to operate in the surveillance setting and makes use of good quality frames from the beginning of the recorded sequence to remove the blur at later stages caused by the dirty lens. A background subtraction method allows us to obtain a stable background of the scene. Based on this background, a multiframe blinddeconvolution algorithm is used to estimate the Point Spread Function (PSF) of the blur. Once the PSF is obtained it can be used to deblur the entire scene. This restoration method was tested on both synthetic and real data with improvements of 15 dB in PSNR being achieved by using clean frames from the beginning of the recorded sequence.
Camera shake during exposure leads to objectionable image blur and ruins many photographs. Conventional blinddeconvolution methods typically assume frequency-domain constraints on images, or overly simplified paramet...
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Camera shake during exposure leads to objectionable image blur and ruins many photographs. Conventional blinddeconvolution methods typically assume frequency-domain constraints on images, or overly simplified parametric forms for the motion path during camera shake. Real camera motions can follow convoluted paths, and a spatial domain prior can better maintain visually salient image characteristics. We introduce a method to remove the effects of camera shake from seriously blurred images. The method assumes a uniform camera blur over the image and negligible in-plane camera rotation. In order to estimate the blur from the camera shake, the user must specify an image region without saturation effects. We show results for a variety of digital photographs taken from personal photo collections.
Passive Millimeter Wave images currently used to detect hidden threats suffer from low resolution, blur, and a very low signal-to-noise-ratio. These shortcomings render threat detection, both visual and automatic, ver...
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ISBN:
(纸本)9781467399623
Passive Millimeter Wave images currently used to detect hidden threats suffer from low resolution, blur, and a very low signal-to-noise-ratio. These shortcomings render threat detection, both visual and automatic, very challenging. Furthermore, due to the presence of very severe noise, most of the blindimage restoration methods fail to recover the system blurring kernel from a single image. In this paper we propose a robust Bayesian multiframe blind image deconvolution method that approximates the posterior distribution of the blur by a Dirichlet distribution. We show that this approach naturally incorporates the non-negativity and normalization constraints for the blur and cope well with the image noise. The performance of the proposed method is tested on both synthetic and real images.
Overlap-blur is caused by the relative movement of high speed between the camera and the object during the exposure process,which is one of the most common phenomenons of image degradation during the criminal detectio...
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Overlap-blur is caused by the relative movement of high speed between the camera and the object during the exposure process,which is one of the most common phenomenons of image degradation during the criminal detection forensics *** on the analysis of the overlap-blurred image’s characteristic,a coded-shutter model is proposed to approximate the nature of overlap-blur. As the first attempt,using the coded-shutter model,an image deblurring algorithm is designed for the restoration of the overlap-blurred *** experiment results show the validity and rationality of the coded-shutter model for deblurring the overlap-blurred *** tested on the real overlap-blurred photographs,the proposed algorithm can restore the information of interest in the blurred images better,which demonstrates the higher practical value of the algorithm.
This paper, describes a new total variation based de-noising scheme. The proposed technique optimally finds the threshold level of the noisy image wavelet decomposition that minimizes the energy of the error between t...
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ISBN:
(纸本)9781467322331
This paper, describes a new total variation based de-noising scheme. The proposed technique optimally finds the threshold level of the noisy image wavelet decomposition that minimizes the energy of the error between the restored and the noisy image. The minimization algorithm is regularized by including 1st as well as 2nd order derivatives effects of the noisy image, into the minimization scheme. Next, the problem of blinddeconvolution of noisy images is addressed. First, the order of the blurring Point Spread Function (PSF), is accurately estimated using a de-noised version of the noisy blurred image. Then, the deconvolution algorithm is modified by including the effects of the 1st as well as 2nd order derivatives of the blurred noisy images into the image update algorithm. Simulation results have shown significant performance improvements of the proposed schemes in both de-noising as well as deblurring noisy image.
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