【作者】 甘小方；

【导师】 钱昆明；

【作者基本信息】 大连理工大学 ， 计算机应用技术， 2006， 硕士

【摘要】 多年来计算机图形处理器(GPU)以大大超过摩尔定律的速度高速发展。图形处理器的发展极大地提高了计算机图形处理的速度和图形质量，并促进了与计算机图形相关应用领域的快速发展。与此同时，图形处理器绘制流水线的高速度和并行性以及近年来发展起来的可编程功能使其在诸如数字图像处理的通用计算领域的应用有着巨大的潜力。图形硬件技术一个最主要的突破就是在图形硬件中引入了可编程功能，此功能允许用户编制自定义的着色器程序(shader program)来替换原来固定流水线中的某些功能模块，使得GPU在功能上更像一个通用处理器。虽然GPU具有非常高的计算速度，但并不能直接将以前在CPU中实现的算法照搬到GPU中来执行，这是因为GPU的指令执行方式和CPU不一样，GPU的体系结构是一种高度并行的单指令多数据(SIMD)指令执行体系。所以要基于可编程图形硬件实现一些在CPU中效率较低的算法，就必须重新组织算法实现的数据结构和步骤，以充分利用GPU并行处理体系结构带来的性能优势。本文中的几种算法都基于可编程图形硬件实现，在达到实时效率的同时保证了结果的质量。 本文首先介绍了GPU的发展历史及GPU的一些技术特点，分析和总结了用GPU实现数字图像处理算法的一些基本框架，介绍了如何通过GPU实现视频的加速处理，并详细地介绍和实现了GPU在边缘检测、颜色空间转换、图像几何变等典型图像处理领域的应用，提出了排序，找最大最小数等算法的GPU中的并行解决方案。 其次，介绍了计算机视觉领域两个很有意义的问题：灰度图像彩色化和颜色传递。首先介绍了此领域的发展过程及一些典型的算法，针对现有的算法速度较慢的问题，提出并实现了基于GPU加速的快速灰度图像彩色化算法和基于GPU加速的颜色传递算法，在取得较好的效果的同时，提高了算法计算速度。 在本文的最后，作者总结了自己关于可编程图形硬件技术的一些经验和体会，并提出了一些未来的研究方向。更多还原

【Abstract】 Graphics processing unit (GPU) has been developing rapidly in recent years at a speed over Moor’s law, and as a result, various applications associated with computer graphics advance greatly. At the same time, the highly processing power, parallelism and programmability available nowadays on the contemporary GPU provide an ideal platform on which the general-purpose such as digital image processing computation could be made. A recent major breakthrough in graphics hardware technology has been the introduction of programmability; this allows the user to replace portions of the fixed graphics pipeline with customized shader programs exposing the ability of GPU to function more like a general processing unit. In spite of all the rendering power, it is not possible or meaningful to use algorithms designed with CPU in mind on graphics hardware. The essential difference is that GPU provides a highly parallel Single Instruction Multiple Data Set (SIMD)architecture. The key to harnessing this resource is reengineering the computationally expensive algorithms to take advantage of this architecture as well as making use of rendering optimizations built into the programmable graphics pipeline. This thesis presents several novel graphics approaches which utilize programmable graphics hardware to obtain both real-time frame rate performance and high quality result.First, the thesis introduced the history and the characters of GPU, drawn a conclusion of image-processing framework based on GPU acceleration, Implemented the program about lots of classic image-processing algorithms, such as border detective, color transferring, geometry transformation, gave the solution how to sort ana find most max or min number with GPU. Introduced how to accelerate video processing with GPU.Second, we introduce another interesting area in Computer Vision field: colorizing greyscale image and color transfer. We introduce the development and some classic algorithms of this area. Then we present a accelerated algorithm of colorizing greyscale image based on GPU and a new algorithm of GPU-Accelerated Color Transfer between Images, which obtain both real-time frame rate performance and high quality result.Finally, I summarize my own research experience of programmable graphics pipeline and propose some potential research topics in the future.更多还原