图像预处理设计与实现
发布时间：2018-11-16 20:49
【摘要】：数字图像处理也被称为计算机图像处理,在居民生活、工业生产、航空航天等领域中占有着重大作用,数字图像预处理是对采集到的图像先进行一系列的处理,以便可以去除图像在传输、数字化过程中产生的一些噪声,并且可以减少图像的无关信息,以便可以更好的对图像进行分析和理解。本文首先介绍了图像预处理平台的硬件搭建,讲述了平台处理器、存储器、电源、复位等硬件组成。研究了可以提取图像特征,简化图像数据量的角点检测算法,并对几种角点检测算法进行了分析研究,针对Harris角点检测算法的不足提出了自适应性的Harris角点检测算法,使用Matlab验证了方案的正确性,改进后的角点检测算法可以更为有效的提取图像的角点信息。其次研究了DCT压缩算法,并针对算法不足之处,提出了自适应性算法,使用Matlab验证了方案的正确性,改进后的算法,可以有效提高算法性能。最后研究了在FPGA上可以应用的一系列的滤波算法,比如图像中值滤波、最小值滤波、最大值滤波、形态学滤波、高斯滤波、Sobel边缘检测滤波,这些滤波方式均可以在FPGA上得以有效实现。
[Abstract]:Digital image processing, also known as computer image processing, plays an important role in the fields of resident life, industrial production, aerospace and so on. In order to remove some noise generated in the process of image transmission and digitization, and to reduce the irrelevant information of the image, so that the image can be better analyzed and understood. This paper first introduces the hardware construction of image preprocessing platform, and describes the hardware composition of platform processor, memory, power supply, reset and so on. The corner detection algorithm which can extract image features and simplify image data is studied. Several corner detection algorithms are analyzed and studied. An adaptive Harris corner detection algorithm is proposed to overcome the shortcomings of Harris corner detection algorithm. The correctness of the scheme is verified by Matlab, and the improved corner detection algorithm can extract corner information more effectively. Secondly, the DCT compression algorithm is studied, and an adaptive algorithm is proposed to overcome the shortcomings of the algorithm. The correctness of the scheme is verified by using Matlab. The improved algorithm can effectively improve the performance of the algorithm. Finally, we study a series of filtering algorithms that can be used in FPGA, such as median image filtering, minimum filtering, maximum filtering, morphological filtering, Gao Si filtering, Sobel edge detection filtering. These filtering methods can be effectively implemented on FPGA.
【学位授予单位】：哈尔滨工程大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.41
本文编号：2336608
[Abstract]:Digital image processing, also known as computer image processing, plays an important role in the fields of resident life, industrial production, aerospace and so on. In order to remove some noise generated in the process of image transmission and digitization, and to reduce the irrelevant information of the image, so that the image can be better analyzed and understood. This paper first introduces the hardware construction of image preprocessing platform, and describes the hardware composition of platform processor, memory, power supply, reset and so on. The corner detection algorithm which can extract image features and simplify image data is studied. Several corner detection algorithms are analyzed and studied. An adaptive Harris corner detection algorithm is proposed to overcome the shortcomings of Harris corner detection algorithm. The correctness of the scheme is verified by Matlab, and the improved corner detection algorithm can extract corner information more effectively. Secondly, the DCT compression algorithm is studied, and an adaptive algorithm is proposed to overcome the shortcomings of the algorithm. The correctness of the scheme is verified by using Matlab. The improved algorithm can effectively improve the performance of the algorithm. Finally, we study a series of filtering algorithms that can be used in FPGA, such as median image filtering, minimum filtering, maximum filtering, morphological filtering, Gao Si filtering, Sobel edge detection filtering. These filtering methods can be effectively implemented on FPGA.
【学位授予单位】：哈尔滨工程大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TP391.41
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