基于稀疏超采样的时间性反走样算法

针对时间性反走样算法在处理帧间复用时,若场景中有较多高频颜色区域或精细模型会造成重 影、模糊、闪烁及子像素细节丢失的问题,提出了基于稀疏超采样的时间性反走样算法。基本思想是,在时间 性反走样算法的基础上,对于无法复用历史帧像素,重新引入空间域的超采样,利用剔除算法以避免不必要的 绘制开销,实现对场景的稀疏超采样。实验结果表明,该算法能够得到与超采样算法媲美的反走样效果,并具 有更高的渲染效率,有效避免重影、模糊、闪烁及子像素细节丢失的问题。      

Subpixel Deblurring of Anti-Aliased Raster Clip-Art

Artist generated clip-art images typically consist of a small number of distinct, uniformly colored regions with clear boundaries. Legacy artist created images are often stored in low-resolution (100x100px or less) anti-aliased raster form. Compared to anti-aliasing free rasterization, anti-aliasing blurs inter-region boundaries and obscures the artist's intended region topology and color palette; at the same time, it better preserves subpixel details. Recovering the underlying artist-intended images from their low-resolution anti-aliased rasterizations can facilitate resolution independent rendering, lossless vectorization, and other image processing applications. Unfortunately, while human observers can mentally deblur these low-resolution images and reconstruct region topology, color and subpixel details, existing algorithms applicable to this task fail to produce outputs consistent with human expectations when presented with such images. We recover these viewer perceived blur-free images at subpixel resolution, producing outputs where each input pixel is replaced by four corresponding (sub)pixels. Performing this task requires computing the size of the output image color palette, generating the palette itself, and associating each pixel in the output with one of the colors in the palette. We obtain these desired output components by leveraging a combination of perceptual and domain priors, and real world data. We use readily available data to train a network that predicts, for each anti-aliased image, a low-blur approximation of the blur-free double-resolution outputs we seek. The images obtained at this stage are perceptually closer to the desired outputs but typically still have hundreds of redundant differently colored regions with fuzzy boundaries. We convert these low-blur intermediate images into blur-free outputs consistent with viewer expectations using a discrete partitioning procedure guided by the characteristic properties of clip-art images, observations about the antialiasing process, and human perception of anti-aliased clip-art. This step dramatically reduces the size of the output color palettes, and the region counts bringing them in line with viewer expectations and enabling the image processing applications we target. We demonstrate the utility of our method by using our outputs for a number of image processing tasks, and validate it via extensive comparisons to prior art. In our comparative study, participants preferred our deblurred outputs over those produced by the best-performing alternative by a ratio of 75 to 8.5.     

The floating column algorithm for shaded, parallel display offunction surfaces without patches

The floating column algorithm is a new method for the shaded rendering of function surfaces. Derived from the monochromatic floating horizon algorithm, it uses the partial derivatives of the function to compute surface normals, thus enabling intensity or normal-interpolation shading. Current rendering methods require tiling the surface with patches, so higher-resolution patching is required for zoom-in views, interactive modification or time-varying surfaces. The new algorithm requires no patching and uses only constant space, so it can be implemented on graphics cards and hand-held devices. Each pixel column is displayed independently of the others, and this "independent column mode" makes the algorithm inherently parallel in the image space, so it is suitable for multiprocessor workstations and clusters and it is scalable in the resolution size. Furthermore, the sampling frequency of the surface can be controlled locally, matching local surface features, distance or artifact elimination requirements. Space-efficient super-sampling for anti-aliasing is also possible. The new algorithm, which allows orthogonal and perspective projections, produces pixel-wide strips which can be displayed in software or hardware. Various extensions are described, including shadows and texture mapping. These properties, together with the algorithm's parallelism, make it potentially useful for the real-time display of functionally-defined textured terrains and the animated display of time-varying surfaces     

基于自适应微调因子的改进frost滤波

为避免frost滤波因使用同一微调因子带来边缘细节等结构信息的模糊,以及等距等权所带来的盲目平滑现象,对frost滤波算法提出了一种改进方案。该方案综合考虑滤波窗口本身的局域统计特性以及窗口内各像素本身的统计特性来自适应确定微调因子。通过对真实合成孔径雷达图像进行改进算法降噪实验,以等效视数和边缘保持指数两项指标为评价标准,并与不同微调因子的Frost滤波输出结果进行比较,结果表明改进算法比原算法有很大的改进,在边缘保持和去噪方面具有更好的滤波性能。     

Novel approach to development of direct volume rendering algorithms based on visualization quality assessment

A novel approach to the development of direct volume rendering algorithms is proposed. The approach is based on the assessment of the visualization quality. Analysis of rendering artifacts and various assessment methods is done using 3D reconstructed medical tomograms as test datasets. Analysis of the previous research on methods of 3D visualization quality assessment and quality improvement is presented. 3D visualization artifacts and quality measurement method (quantitative estimation) is proposed. The method does not require any ground truth image; hence, it is a universal approach to measure the quality of the 3D-reconstruction by any ray casting technique. The method is based on generation of the reference image as a mathematical expectation for a set of 3D visualizations obtained via the jittering technique. Start position of the rays are being shifted randomly towards their directions. To estimate the deviation of a pixel value from mathematical expectation, we use PSNR metrics, which is traditional metrics in signal and image processing and measures deviation in the decibel scale. The conditions of a proper use of the technique are discussed. A new virtual samplings method with preintegration is proposed to reduce sampling artifacts in the ray casting algorithm. The novelty of the method consists in using pre-integrated classification instead of post-classification in the virtual sampling method. A novel approach to 3D visualization algorithms development based on analysis of a ray casting method in quality-performance space is demonstrated by comparing the state-of-the-art ray casting methods and the proposed method. The comparative analysis revealed an advantage of the classical pre-integrated method in the case of using trilinear filtering without local shading. It also showed the advantage of the proposed virtual sampling method with pre-integration in the case of using tricubic filtering with local lighting.     

A Euclidean distance transform using grayscale morphologydecomposition

A fast and exact Euclidean distance transformation using decomposed grayscale morphological operators is presented. Applied on a binary image, a distance transformation assigns each object pixel a value that corresponds to the shortest distance between the object pixel and the background pixels. It is shown that the large structuring element required for the Euclidean distance transformation can be easily decomposed into 3×3 windows. This is possible because the square of the Euclidean distance matrix changes uniformly both in the vertical and horizontal directions. A simple extension for a 3D Euclidean distance transformation is discussed. A fast distance transform for serial computers is also presented. Acting like thinning algorithms, the version for serial computers focuses operations only on the potential changing pixels and propagates from the boundary of objects, significantly reducing execution time. Nonsquare pixels can also be used in this algorithm. An example application, shape filtering using arbitrary sized circular dilation and erosion, is discussed. Rotation-invariant basic morphological operations can be done using this example application     

关于图像反走样的理论及应用

图像反走样是用于提升图像质量的一个重要环节。导致图像失真的主要原因是由于采样频率过低及重建过滤器的质量低下。在实时渲染的应用中,随着硬件的发展及渲染架构的改变,主流反走样技术逐渐从硬件加速模式发展到后处理模式。纯后处理算法由于缺失子像素信息,无法生成高质量的反走样图像。针对这一问题,混合反走样在保留了后处理反走样效率的同时,通过结合多重采样能提供更精确的边缘处理,并保证图像在时序上的稳定性。     

基于延迟着色与动态目标光效应的航空场景反走样算法

针对航空仿真中的视景画面走样问题,提出一种基于延迟着色与动态目标光效应的反走样算法。首先,针对宏观静态场景,综合利用法线信息与位置信息提取场景的边缘区域,通过抖动采样对边缘进行平滑处理,并采用一定倍数的超采样进行反走样结果优化;其次,在上一步的基础上,针对场景中的动态目标,建立几何变换与光效应的数学模型,通过计算动态目标伪距离和动态目标在虚拟场景中的位置坐标确定最终的显示效果,以解决动态目标在实时运动中走样和像素丢失的问题。最后,在某型号飞行仿真平台进行了算法验证。实验结果表明该算法能够解决航空仿真中静态场景和动态目标的走样问题,适用于航空仿真训练。     

基于数据修正的实时阴影反走样算法

基于百分比渐近滤波（PCF）算法,提出一种改进的实时阴影反走样算法——数据修正PCF算法,其主要思想是在双线性插值滤波前对插值的数据进行必要的修正,从而消除阴影中的一些锯齿形走样现象．该算法利用像素渲染器PS2．0在图形硬件上实现．从实例图片可以看出,文中算法产生的许多阴影边界走样现象得到了明显的改善．     

New spatial based MRI image de-noising algorithm

Nowadays, fast scan techniques are used to reduce scanning times. These techniques raise scanning noise level in MRI systems. Instead of progress made in image de-noising, still, it is challenging. A novel edge-preserving neighbourhood filter for image enhancement is proposed. The main focus of this paper is to propose an adaptive filtering function to account for the image content while try to preserve edge of image. Proposed algorithm uses the edges of image to do edge-preserving neighbourhood filtering. Contribution of a sample, in neighbourhood of a pixel, in filtering, depends on the space between the pixel and the sample. In fact, the sample which there is edge between it and the pixel don’t contribute in the grey level estimation. Promising experimental results on simulated and real brain images and comparison with state-of-art de-noising algorithm demonstrate the potential of proposed algorithm.     

Revectorization-Based Soft Shadow Mapping

In this paper, we present revectorization-based soft shadow mapping, an algorithm that enables the rendering of visually plausible anti-aliased soft shadows in real time. In revectorization-based shadow mapping, shadow silhouettes are anti-aliased and filtered on the basis of a discontinuity space. By replacing the filtering step of the theoretical framework of the percentage-closer soft shadow algorithm by a revectorization-based filtering algorithm, we are able to provide anti-aliasing mainly for near contact shadows or small penumbra sizes generated from low-resolution shadow maps. Moreover, we present a screen-space variant of our technique that generates visually plausible soft shadows with an overhead of only in processing time, when compared to the fastest soft shadow algorithms proposed in the literature, but that introduces shadow overestimation artefacts in the final rendering.     

一种快速高效的反走样算法*

快速近似反走样是一种后处理式反走样技术,其效果好、效率高,但由于是根据亮度值检测边缘,导致模型纹理贴图上的条纹和高光部分也会被检测出来,从而造成不必要的反走样。针对这一问题,该算法提出了一种改进的反走样方法:根据物理和阴影信息检测出模型与阴影边缘,再以边缘周围状况计算确定混合朝向,最后结合亚像素覆盖率进行反走样运算。实验表明,该算法在保留了原快速近似反走样效率的同时,有效地消除了不必要的反走样。     

圆的整数反走样生成算法

针对现有圆的反走样生成算法计算复杂,反走样效果一般的缺点,提出一种基于中点画圆法的整数反走样生成算法。该算法根据像素中心到理想圆弧的距离来分配灰度,生成64级灰度的反走样圆弧。通过省略二次项来简化计算,并用简单的计算修正省略带来的误差以保证精度。为了简化计算,提出相邻像素的灰度递推方法,利用整数移位、加法、比较来实现反走样。该算法结构简单,反走样效果较好,由于避免了浮点和除法运算,便于硬件实现。     

光线追踪等价划分反锯齿算法

为了解决图形处理过程中出现的锯齿问题,本文提出了一种高效的光线追踪等价划分反锯齿算法。算法通过计算相邻像素采样点间颜色偏差,对偏差超过阈值的边界采样点进行递归划分为更小的不规则区域,对偏差小于阈值的采样点不进行分解,用中点颜色取代区域颜色,保证反锯齿效果同时减少采样点的个数。进过仿真实验表明本文算法反锯齿效果与超采样反锯齿效果相同,但采样点数减少39.70%,计算效率提高43.26%。     

Visual tracking of known three-dimensional objects

A method is described of visually tracking a known three-dimensional object as it moves with six degrees of freedom. The method uses the predicted position of known features on the object to find the features in images from one or more cameras, measures the position of the features in the images, and uses these measurements to update the estimates of position, orientation, linear velocity, and angular velocity of the object model. The features usually used are brightness edges that correspond to markings or the edges of solid objects, although point features can be used. The solution for object position and orientation is a weighted least-squares adjustment that includes filtering over time, which reduces the effects of errors, allows extrapolation over times of missing data, and allows the use of stereo information from multiple-camera images that are not coincident in time. The filtering action is derived so as to be optimum if the acceleration is random. (Alternatively, random torque can be assumed for rotation.) The filter is equivalent to a Kalman filter, but for efficiency it is formulated differently in order to take advantage of the dimensionality of the observations and the state vector which occur in this problem. The method can track accurately with arbitrarily large angular velocities, as long as the angular acceleration (or torque) is small. Results are presented showing the successful tracking of partially obscured objects with clutter.     

粗糙集在图像边缘增强滤波中的应用

为使图像噪声滤除的同时,边缘细节信息能得到有效地保护,基于粗糙集理论介绍了一种新的边缘增强滤波方法。首先,基于粗糙集不可分辨等价关系划分,分离出噪声点和非噪声点,对噪声点通过中值滤波进行滤除,然后,通过粗近似精度和方向模板检测边缘的连续性和方向,以具有最大粗近似精度的模板的灰度均值取代中心像素点灰度。在所有进行边缘检测的滤波算法中,该算法是唯一边缘测度在多次迭代运行后不会减小的滤波方法,同时通过对不同噪声程度的椒盐噪声和高斯噪声的滤波实验,说明该方法在有效滤除噪声同时能使边缘细节得到保护和增强,且比其它传统的空域和频域滤波方法具有更好的噪声适应性。     

采用面积采样的反走样字符旋转算法

目的 针对现有字符反走样算法中灰度分配不准确导致的字符抖动、实时性较差等问题,提出一种高效的反走样算法.方法 首先,算法基于面积采样原理,根据周围邻域的像素点来分配灰度,使像素点的坐标定位更加准确,从而解决了字符动态显示时抖动的问题;其次,通过反向坐标变换消除了字符旋转后出现的空洞现象;最后,算法充分利用了FPGA的并行计算能力,在时间和空间上都做到了优化.结果 实验结果表明,本文算法很好地解决了字符抖动问题,并且新算法的仿真速度约为传统算法的6倍以上,比五株排列算法提高了30%.结论 相比其他算法,新算法的优势体现在两个方面,一是字符的灰度过渡平滑,反走样效果更好;二是速度快,实时性高,新算法适用于工程中各种场合下点阵字符的显示,尤其是实时性要求高的环境.     

一种基于小波变换图像去噪的方法

提出了一种基于图像软阈值小波变换的高斯白噪声消除法。该算法根据含噪声图的特点,把信号分成信号象素与可能噪声象素两类,对于可能是噪声的象素,采用图像的小波软阈值去噪方法进行滤波,而对信号象素不产生影响,且能保留更多的图像细节。文中也给出了标准中值滤波,自适应维纳滤波算法和小波软阈值去噪的算法进行比较实验,结果表明用小波软阈值去噪的算法处理高度污染高斯白噪声的图像能力明显强于标准中值滤波,稍微优于自适应维纳滤波算法,且能够比较好保留图像的细节部分。     

多光谱遥感影像建筑物提取

针对传统遥感影像目标提取对数据要求严格及应用受限的问题,提出一种基于非线性尺度空间滤波的建筑物提取算法.首先,构造多光谱影像各个波段的非线性尺度空间并进行迭代滤波;然后,搜索全局影像的标准差曲线的第一个谷点,停止迭代过程;最后,利用最大类间方差法分别对各个波段的滤波结果进行二值化.为了验证本文方法的有效性,选取福州市的一幅航空影像,并与同类方法进行对比.试验结果表明,本文算法能在平滑噪声的同时保留建筑物边缘信息,对于提取排列紧密的建筑物有更好的效果,在保证查准率的前提下,查全率有5%以上的提高.