Markov random field model-based edge-directed image interpolation.

This paper presents an edge-directed image interpolation algorithm. In the proposed algorithm, the edge directions are implicitly estimated with a statistical-based approach. In opposite to explicit edge directions, the local edge directions are indicated by length-16 weighting vectors. Implicitly, the weighting vectors are used to formulate geometric regularity (GR) constraint (smoothness along edges and sharpness across edges) and the GR constraint is imposed on the interpolated image through the Markov random field (MRF) model. Furthermore, under the maximum a posteriori-MRF framework, the desired interpolated image corresponds to the minimal energy state of a 2-D random field given the low-resolution image. Simulated annealing methods are used to search for the minimal energy state from the state space. To lower the computational complexity of MRF, a single-pass implementation is designed, which performs nearly as well as the iterative optimization. Simulation results show that the proposed MRF model-based edge-directed interpolation method produces edges with strong geometric regularity. Compared to traditional methods and other edge-directed interpolation methods, the proposed method improves the subjective quality of the interpolated edges while maintaining a high PSNR level.     

一种边缘定向平滑图像插值算法

针对传统图像放大算法边缘处理效果较差,自适应图像插值方法存在高计算复杂度的问题,该文提出一种有效增强图像边缘轮廓的插值放大算法。该算法结合边缘定向平滑滤波器和双线性插值的特点,使得图像在平坦和非平坦区域均能取得理想效果。仿真测试结果表明,与基于统计特征的自适应插值算法相比,该文提出算法能显著提高插值速度,平均运行时间降低8.33 s;与双三次插值算法相比,图像峰值信噪比平均增加0.30 dB。     

一种基于边缘判决的空域差错掩盖算法

提出了一种基于边缘判决的解码视频空域差错掩盖算法。该算法首先对丢失块邻域中的像素进行边缘检测,并对检测出的边缘判断其是否会穿过丢失块。然后使用方向选择过程提取多个候选插值方向,并通过边界像素灰度差决定最终插值方向。实验结果表明本算法有效地提高了错误图像的掩盖效果。     

基于二进小波变换的边缘保持图像插值算法

利用离散二进小波变换(DDWT)所具有的良好的多尺度边缘提取特性以及子带间的相关性,提出了基于DDWT的边缘保持图像插值算法。算法利用多尺度边缘的指数衰减规律预测损失掉的高频子带中的边缘,并利用三次样条插值算法恢复损失掉的高频子带中的非边缘信息。最后通过离散二进小波合成得到高分辨率图像。实验结果显示,该算法优于传统的双线性和双三次插值算法。对于像Lena这样的纹理较少的图像其峰值信噪比(PSNR)提高了2dB以上,而对其它图像插值的结果也有不同程度的质量改善,插值的结果更符合人的视觉系统特性。     

基于结构成分双向扩散的图像插值算法

该文提出一种基于结构成分双向扩散的插值方法,有效地减小了插值图像的边缘扩散,从而获得更为清晰的边缘。该方法采用改进的耦合双向扩散滤波器对轮廓模板插值图像进行边缘增强。其中,为了使滤波器更精确地作用于边缘轮廓,利用形态成分分析(MCA)分离出初始插值图像中的结构分量再实行滤波;同时,改进双向扩散模型,使其能够根据边缘梯度自适应地调整边缘扩散程度,且更加柔和地控制梯度方向的像素值变化。实验结果表明,对比传统的插值方法、相关的边缘自适应插值方法以及几种应用普遍的商用软件,该方法获得的插值图像主、客观质量均有明显提升,不仅有效提高图像锐度,且边缘光滑、过渡自然,避免产生边缘锯齿和过度的人工效应。     

Subpixel edge localization and the interpolation of still images

In this paper, we present a nonlinear interpolation scheme for still image resolution enhancement. The algorithm is based on a source model emphasizing the visual integrity of detected edges and incorporates a novel edge fitting operator that has been developed for this application. A small neighborhood about each pixel in the low-resolution image is first mapped to a best-fit continuous space step edge. The bilevel approximation serves as a local template on which the higher resolution sampling grid can then be superimposed (where disputed values in regions of local window overlap are averaged to smooth errors). The result is an image of increased resolution with noticeably sharper edges and, in all tried cases, lower mean-squared reconstruction error than that produced by linear techniques.     

基于小波的双线性插值误差补偿算法的图像放大

为了尽可能地保持低分辨率图像的基本信息,提高图像的视觉效果和空间分辨率,本文提出一种基于小波的双线性插值误差补偿算法。该算法增加双线性插值的误差补偿项,利用Sobel算子设定插值点的边缘方向,得到初始放大图像。利用小波提取高频成分,原始图像幅值增强充当低频部分,再经过小波逆变换得到高分辨率图像。实验结果表明,相对于传统的图像放大算法,该算法考虑到全局相关性,得到更加清晰的边缘信息。     

Morphological Image Enlargements

This paper presents a method based in mathematical morphology to enlarge images. It does not make the low pass assumption which is common to all linear interpolation methods and which does not often hold for images. Pixels in smooth areas are properly interpolated by linear methods while those at the edges are not. The method begins with a linear interpolation and a gradient computation. The gradient serves as a measure of confidence about the linear interpolation. Then, the proposed algorithm processes the pixels in a certain order: first pixels with high confidence (smooth zones) of the image and those with a low one (edges) at the end. By doing so, it preserves both slow variations and sharp edges. The method can be applied to other image processing problems, such as edge enhancement or motion vector estimation, where there is an image and confidence information about each pixel.     

自适应图像插值的Hermite型混合样条方法

分析了Hermite型插值样条的基本特性,研究了图像放大时边缘区域产生模糊的原因,并考虑到数字图像实时传输的要求,给出了一类新的自适应图像插值算法.　由于采用单核插值以及弹性边界的处理方法,提出的算法计算复杂性较小,且尽可能保持了边缘像素原有特征. 数值模拟与仿真显示该方法比传统方法有更清晰的边界.     

Feature preserving image interpolation by adaptive bidirectional flow

Most image interpolation algorithms currently used suffer visually to some extent the effects of blurred edges and jagged artifacts in the image. This letter presents an adaptive feature preserving bidirectional flow process, where an inverse diffusion is performed to enhance edges along the normal directions to the isophote lines （edges）, while a normal diffusion is done to remove artifacts （＂jaggies＂） along the tangent directions. In order to preserve image features such as edges, angles and textures, the nonlinear diffusion coefficients are locally adjusted according to the first order and the second order directional derivatives of the image. Experimental results on the Lena image demonstrate that our interpolation algorithm substantially improves the subjective quality of the interpolated images over conventional interpolations.     

Edge-forming methods for color image zooming.

This paper introduces edge-forming schemes for image zooming of color images by general magnification factors. In order to remove/reduce artifacts arising in image interpolation, such as image blur and the checkerboard effect, an edge-forming method is suggested to be applied as a postprocess of standard interpolation methods. The method is based on nonconvex nonlinear partial differential equations. The equations are carefully discretized, incorporating numerical schemes of anisotropic diffusion, to be able to form reliable edges satisfactorily. The alternating direction implicit (ADI) method is employed for an efficient simulation of the model. It has been numerically verified that the resulting algorithm can form clear edges in 2 to 3 ADI iterations. Various results are given to show th eeffectiveness and reliability of the algorithm.     

Statistical Study of Edges in TV Pictures

The present study is devoted to the statistical analysis of edges in still monochrome TV pictures. The visual information carried by the edges is especially important both for image interpretation and for subjective image quality evaluation. Statistical knowledge on edges is helpful to improve image coding techniques significantly as well as processing techniques for scene analysis. After an introduction on nonstationary local statistical models, we describe the parameters of edges and the methods used to measure them. Statistical data collected on these parameters are then presented. The data concern orientation, edge length, edge width, runlength between edges and edge slope probability distributions as well as the measure of orientation continuity along an edge and the relative frequencies of edge pixels and contrasted isolated pixels.     

Adaptively quadratic (AQua) image interpolation

Image interpolation is a key aspect of digital image processing. This paper presents a novel interpolation method based on optimal recovery and adaptively determining the quadratic signal class from the local image behavior. The advantages of the new interpolation method are the ability to interpolate directly by any factor and to model properties of the data acquisition system into the algorithm itself. Through comparisons with other algorithms it is shown that the new interpolation is not only mathematically optimal with respect to the underlying image model, but visually it is very efficient at reducing jagged edges, a place where most other interpolation algorithms fail.     

基于边缘的实时视频缩放引擎的设计与实现

提出了一种基于边缘自适应插值算法的缩放引擎有效的设计方法,并通过FPGA验证。首先介绍了自适应插值算法的基本原理,接着提出了优化设计的缩放引擎系统结构,并系统的论述了数据缓冲模块的实现及高效的运算系数生成模块和插值计算模块。最后在FPGA上验证了该系统,结果表明,运用该算法插值获得了边缘清晰的目标图像,且该算法复杂度低,因此,适应于实时条件下的图像缩放。     

基于蚁群算法和线段分析的建筑物特征提取

针对航拍图像分辨率低,背景复杂等特点,研究了基于蚁群算法和线段分析的航拍图像建筑物识别方法.将蚁群算法首次运用到航拍图像的边缘提取上,在提取出目标的同时有效将干扰去除.根据蚁群算法提取的边缘连续性差的特点,利用直线的链码特征提取直线段,并在原始任明武链码跟踪算法的基础上设定首次跟踪方向和设置新的跟踪规则及新的链码分裂规则,使算法适合直线的跟踪与提取.将提取出的短直线段进行直线段的合并.最后用搜索矩形元的方法提取矩形建筑物.通过实验证明算法取得了很好的效果.     

三维B超医学图像插值重构研究

本文讨论了图像插值在超声图像三维重建中的应用,着重于在进行可视化之前如何利用合适的插值算法把三维规则不均匀数据场转换为三维规则均匀数据场,提出有偏距离加权同心插值,并从峰值信噪比、归一化互相关系数和运算速度等几个方面与线性插值,三次插值以及高斯插值等三种较典型的插值算法进行了比较。     

Study on infrared image super-resolution reconstruction based on an improved POCS algorithm

Aiming at the disadvantages of the traditional projection onto convex sets of blurry edges and lack of image details, this paper proposes an improved projection onto convex sets (POCS) method to enhance the quality of image super-resolution reconstruction (SRR). In traditional POCS method, bilinear interpolation easily blurs the image. In order to improve the initial estimation of high-resolution image (HRI) during reconstruction of POCS algorithm, the initial estimation of HRI is obtained through iterative curvature-based interpolation (ICBI) instead of bilinear interpolation. Compared with the traditional POCS algorithm, the experimental results in subjective evaluation and objective evaluation demonstrate the effectiveness of the proposed method. The visual effect is improved significantly and image detail information is preserved better.     

Edge-directed interpolation based on shifted-linear image model

This paper presents a hybrid image interpolation algorithm to keep details and edges simultaneously. The basic idea is to separate the unknown pixels into two classes and estimate them in different way. One class of unknown pixels is obtained via shifted linear interpolation and the other class through statistical signal processing method. The merit of this hybrid algorithm is that each unknown pixel can be estimated through original pixels simultaneously. Simulation results demonstrate that this hybrid interpolation algorithm improves the quality of the interpolated images over conventional interpolation methods.     

Saturation-based adaptive inverse gradient interpolation for Bayerpattern images

A saturation-based adaptive gradient interpolation algorithm is developed for Bayer pattern images obtained in single-sensor digital cameras. The proposed algorithm uses the concept of pseudo-saturation for 2×2 blocks of the image. The algorithm adapts the scheme of interpolation based on the classification of the pseudo-saturation of Bayer pattern images. Compared with other algorithms, the proposed method preserves fine details, reduces false colours, and distortions around edges and sharp features of the colour image reconstructed from different kinds of Bayer pattern images     

Adaptive resampling algorithm for image zooming

Applying an interpolation function indiscriminately to an image, to resample it, will generally result in aliasing, edge blurring and other artefacts. The authors present an adaptive resampling algorithm for zooming up images. The algorithm is based on analysing the local structure of the image and applying a near optimal and least time-consuming resampling function will preserve edge locations and their contrast. This is done by segmenting the image dynamically into homogeneous areas, as it is scanned or received. Based on the location of the pixel to be computed (whether it is within a homogenous area, is on its edge or is an isolated feature), interpolation, extrapolation or pixel replication is chosen. The algorithm performance, from both a quality and a computational complexity aspect, are compared to different methods and functions previously reported in the literature. The advantage of the algorithm is quite apparent at edges and for large zooming factors