Design of a new restoration algorithm based on the constrained mean-square-error criterion

In this paper the joint optimization of different criteria is addressed, as a powerful means of incorporatinga priori information in linear image-restoration algorithms. Theconstrained mean-square-error (CMSE) approach is introduced, which enables the incorporation of both spatial and spectral information regarding the peculiarities of the problem. Depending on the nature of the spatial information, this approach can be interpreted as either a regularized or an adaptive scheme. As a regularized scheme, it offers an alternative to conventional approaches, in which the ringing artifacts are efficiently suppressed by means of the regularizing operator. As an adaptive scheme, the CMSE approach offers the flexibility of applying either linear Wiener filtering or inverse filtering, depending on the local signal activity. Optimal techniques for the selection of the regularization parameter in both nonadaptive and adaptive cases are introduced. The capabilities of the CMSE approach as a regularized scheme and an adaptive scheme, are demonstrated through restoration examples.     

从甘肃民勤生态危机反思石羊河流域水资源利用模式

民勤生态环境危机主要表现在:土地盐碱化、荒漠化日益严重,灾害性天气频繁发生等方面,这些都直接威胁着绿洲存亡。从绿洲生态危机对石羊河流域水资源利用模式进行了反思,指出了目前流域水资源利用中存在的问题,并提出了建议:实行流域水资源统一管理;建立合理的水权制度,适当调整水价;控制人口增长;加快外流域调水。     

贵州省岩溶地区水土资源生态安全研究

基于压力-状态-响应(PSR)模型,利用相对距离和层次分析方法对贵州省2007~2012年的水土资源生态安全进行定量化分析。结果表明,2007~2012年贵州省的水土资源压力安全距离和状态安全距离总体偏小,响应安全距离相对较大;总体生态安全属于安全状态,响应安全距离较大是影响总体安全距离的主要因素;水土资源生态安全的最大影响因素是水土资源开发利用的管理。该结果可为贵州省水土资源的可持续利用、生态环境建设和经济社会发展提供借鉴和参考。     

Models of Restoration Probability in WDM Networks Employing Active Restoration

The ever-increasing demand for network bandwidth makes network survivability an issue of great concern. Lightpath restoration is a valuable approach to guaranteeing an acceptable level of survivability in WDM optical networks with better resource utilization than that of its protection counterpart. Active restoration (AR) is a newly proposed lightpath restoration scheme [M. Mostafa et al. OSA Journal of Optical Networking, vol. 3, no. 4, pp. 247–260] that combines the best of protection and reactive restoration while avoiding their shortcomings. In this paper, we conduct detailed performance analysis on the restoration probability of AR-based WDM networks. In particular, analytical models of restoration probability are developed respectively for networks with full-wavelength conversion capability and for networks without wavelength conversion capability under different backup path searching schemes. Based on the new models, we investigate the effects of wavelength availability, wavelength conversion capability, path length as well as backup path seeking methods on the restoration probability.     

古地貌恢复方法综述

古地貌形态控制着沉积相类型和展布,从而控制油气藏的生储盖组合,因此,古地貌的准确恢复对油气勘探具有非常重要的意义。在前人研究的基础之上,利用高分辨率层序地层学法、双界面法、回剥和填平补齐法、构造沉积模拟法和沉积期微幅度古地貌推算法对古地貌恢复方法进行总结,结果表明,小区域内可利用双界面法进行古地貌恢复,对于构造运动强烈地区,应采用构造沉积模拟法,而针对一些微幅构造地区,沉积期微幅度古地貌推算法能较为准确地恢复古地貌。     

An efficient framework for image/video inpainting

Image inpainting has been widely applied to many applications, such as restoring corrupted old photos, erasing video logos, concealing errors in a digital video processing system, and so on. However, traditional geometric inpainting methods suffer low efficiency. To tackle this problem, this paper addresses an efficient transform based framework for geometric methods. Given an image, we firstly decompose it, then separately perform restoration process and finally employ Laplacian diffusion function to hold local texture coherence. Experimental results show that the proposed method not only speeds up and enhances the performances of geometric methods, but also obtains a better restoration results compared with the traditional texture and hybrid methods.     

基于纹理覆盖的静止图像数据恢复

块编码图像传统中因噪声干扰会引起缺损,对此本文提出一种修复缺损数据的方法。对含有数据缺损的局部域图像。以纹理覆盖方式在缺损区生成新数据,较好地解决了边界连续和纹理一致的问题,模拟实验显示出该方法的有效性。     

A novel image restoration scheme based on structured side information and its application to image watermarking

This paper presents a new image restoration method based on a linear optimization model which restores part of the image from structured side information (SSI). The SSI can be transmitted to the receiver or embedded into the image itself by a digital watermarking technique. In this paper we focus on a special type of SSI for digital watermarking where the SSI is composed of mean values of 4×4 image blocks which can be used to restore manipulated blocks. Different from existing image restoration methods for similar types of SSI, the proposed method minimizes image discontinuity according to a relaxed definition of smoothness based on a 3×3 averaging filter of four adjacent pixel value differences, and the objective function of the optimization model has a second regularization term corresponding to a second-order smoothness criterion. Our experiments on 100 test images showed that given complete information of the SSI, the proposed image restoration technique can outperform the state-of-the-art model based on a simple linear optimization model by around 2 dB in terms of an average Peak Signal-to-Noise Ratio (PSNR) value and around 0.04 in terms of a Structural Similarity Index (SSIM) value. We also tested the robustness of the image restoration method when it is applied to a self-restoration watermarking scheme and the experimental results showed that it is moderately robust to errors in SSI (which is embedded as a watermark) caused by JPEG compression (the average PSNR value remains above 16.5 dB even when the JPEG QF is 50), additive Gaussian white noises (the average PSNR value is approximately 18.4 dB when the noise variance σ² is 10) and image rescaling assuming the original image size is known at the receiver side (e.g. the average PSNR value is approximately 19.6 dB when the scaling ratio is 1.4).     

基于边界像素的模糊模型复原研究

针对水平方向匀速直线运动模糊一般模型进行复原时存在明显周期干扰的问题,从分析边缘像素的角度出发,提出了基于零边界像素的复原模型和基于Neumann边界像素的复原模型,有效的减轻了周期干扰.通过广义逆矩阵进行运动模糊图像的复原,从实验结果来看,本文的复原方法简单可行,并具有较好的复原效果.     

A rapid hybrid algorithm for image restoration combining parametric Wiener filtering and wave atom transform

Image restoration refers to removal or minimization of known degradations in an image. This includes de-blurring images degraded by the limitations of sensors or source of captures in addition to noise filtering and correction of geometric distortion due to sensors. There are several classical image restoration methods such as Wiener filtering. To find an estimate of the original image, Wiener filter requires the prior knowledge of the degradation phenomenon, the blurred image and the statistical properties of the noise process. In this work, we propose a new rapid and blind algorithm for image restoration that does not require a priori knowledge of the noise distribution. The degraded image is first de-convoluted in Fourier space by parametric Wiener filtering, and then, it is smoothed by the wave atom transform after setting the threshold to its coefficients. Experiment results are significant and show the efficiency of our algorithm compared with other techniques in use.