本文设计的基于FPGA的图像处理系统，是一个具有视频图像采集、图像处理、图像 显示功能的图像处理系统。该系统采用Altera公司FPGA芯片作为中央处理器，由视频解 码模块、图像处理模块、视频编码模块组成。模拟视频信号由CCD传感器送入，经视频 解码芯片SAA7113转换成数字视频信号后，图像处理模块完成中值滤波和边缘检测这两种 图像处理算法，视频编码芯片SAA7121将数字视频信号转换成模拟视频信号输出。

基于FPGA的图像处理论文集合，视频采集、压缩、消旋等图像处理的应用 一个100多篇

随着科学技术的不断发展,工业生产也逐渐由人力向机器自动化转变。机器视觉检测系统作为工业自动化领域的重要分支之一,其结构可分为图像采集系统以及机械系统。其中图像采集系统所采集到的图像质量会直接影响着检测的效率与质量,目前国外在这个方面的研究较多,国内在这些方面的研究和国外相比还有一定的差距。为了提升图像采集系统的应用范围以及精确度,本课题设计了以FPGA为控制核心的图像采集系统。本实验室原有的图像采集系统多针对非接触式测量设计,且采用的都是黑白线阵CCD,因而在扫描方面的使用范围上就有诸多的限制。故本文的目的是设计一种以彩色线阵CCD作为图像传感器的图像采集系统。该系统不仅能应用于非接触式测量,还能用于诸多的扫描检测场景中。在系统设计过程中,首先设计了系统的整体方案,并将整个系统划分为图像采集模块、数模转换模块、主控模块、电源模块以及数据输出模块。在分析每个模块的具体需求的基础上,对主要芯片进行了选型,如采用TCD2252D作为图像传感器,AD9822作为AD转换芯片,EP4CE6E22C8N作为主控芯片。此后,根据元器件的特性以及电路原理对各个模块的具体电路进行了设计,并根据PCB的设计原则以及元器件的封装信息设计并制作了系统的电路板。软件方面,在Quartus II环境下,使用Verilog HDL语言编写了CCD驱动、AD驱动、AD配置,并对FIFO进行了配置,使用modelsim对系统软件进行了仿真调试。通过硬件及软件的设计,基本完成了图像采集系统的设计。将系统软件下载到电路板中,用示波器观察到了稳定的输出信号,说明本系统的软硬件设计无误,系统能够稳定的工作,达到了设计目的。

通过ov5640拍摄图像，存储与sdram，再从sdram种读取并显示

文档介绍了用FPGA来实现数字图像的处理，是图像处理领域的热门。

介绍了一种视频检测中图像预处理系统的设计方案,实现了具有前 端视频采集!图像预处理功能的FPGA子系统"该系统采用Altera公司的FPGA芯片 作为中央处理器,由视频采集模块!异步FFIO模块!视频解码模块!工e配置接 口模块!图像帧存控制模块!图像低级处理模块!通信接口模块和FPGA配置电路 组成"模拟视频信号由CDC传感器送入,经视频AD/芯片S从7113转换成数字视频 信号后,送入到异步F工FO中缓冲"视频解码模块采用对视频流数据识别的方法获 得图像数据,然后送入帧存储器"图像低级处理模块预处理图像数据并经通信接 口送到后端数字信号处理器做进一步图像检测"

很好很全的FPGA嵌入式图像处理开发资料，有很强的应用价值，如果您对这方面感兴趣，我想您一定会喜欢的！

Preface xi Acknowledgements xvii 1 Image Processing 1 1.1 Basic Definitions 2 1.2 Image Formation 3 1.3 Image Processing Operations 7 1.4 Example Application 9 1.5 Real-Time Image Processing 11 1.6 Embedded Image Processing 12 1.7 Serial Processing 12 1.8 Parallelism 14 1.9 Hardware Image Processing Systems 18 2 Field Programmable Gate Arrays 21 2.1 Programmable Logic 21 2.1.1 FPGAs vs. ASICs 24 2.2 FPGAs and Image Processing 25 2.3 Inside an FPGA 26 2.3.1 Logic 27 2.3.2 Interconnect 28 2.3.3 Input and Output 29 2.3.4 Clocking 30 2.3.5 Configuration 31 2.3.6 Power Consumption 32 2.4 FPGA Families and Features 33 2.4.1 Xilinx 33 2.4.2 Altera 38 2.4.3 Lattice Semiconductor 44 2.4.4 Achronix 46 2.4.5 SiliconBlue 47 2.4.6 Tabula 47 2.4.7 Actel 48 2.4.8 Atmel 49 2.4.9 QuickLogic 50 2.4.10 MathStar 50 2.4.11 Cypress 51 2.5 Choosing an FPGA or Development Board 51 3 Languages 53 3.1 Hardware Description Languages 56 3.2 Software-Based Languages 61 3.2.1 Structural Approaches 63 3.2.2 Augmented Languages 64 3.2.3 Native Compilation Techniques 69 3.3 Visual Languages 72 3.3.1 Behavioural 73 3.3.2 Dataflow 73 3.3.3 Hybrid 74 3.4 Summary 77 4 Design Process 79 4.1 Problem Specification 79 4.2 Algorithm Development 81 4.2.1 Algorithm Development Process 82 4.2.2 Algorithm Structure 83 4.2.3 FPGA Development Issues 86 4.3 Architecture Selection 86 4.3.1 System Level Architecture 87 4.3.2 Computational Architecture 89 4.3.3 Partitioning between Hardware and Software 93 4.4 System Implementation 96 4.4.1 Mapping to FPGA Resources 97 4.4.2 Algorithm Mapping Issues 100 4.4.3 Design Flow 101 4.5 Designing for Tuning and Debugging 102 4.5.1 Algorithm Tuning 102 4.5.2 System Debugging 104 5 Mapping Techniques 107 5.1 Timing Constraints 107 5.1.1 Low Level Pipelining 107 5.1.2 Process Synchronisation 110 5.1.3 Multiple Clock Domains 111 5.2 Memory Bandwidth Constraints 113 5.2.1 Memory Architectures 113 5.2.2 Caching 116 5.2.3 Row Buffering 117 5.2.4 Other Memory Structures 118 vi Contents 5.3 Resource Constraints 122 5.3.1 Resource Multiplexing 122 5.3.2 Resource Controllers 125 5.3.3 Reconfigurability 130 5.4 Computational Techniques 132 5.4.1 Number Systems 132 5.4.2 Lookup Tables 138 5.4.3 CORDIC 142 5.4.4 Approximations 150 5.4.5 Other Techniques 152 5.5 Summary 154 6 Point Operations 155 6.1 Point Operations on a Single Image 155 6.1.1 Contrast and Brightness Adjustment 155 6.1.2 Global Thresholding and Contouring 159 6.1.3 Lookup Table Implementation 162 6.2 Point Operations on Multiple Images 163 6.2.1 Image Averaging 164 6.2.2 Image Subtraction 166 6.2.3 Image Comparison 170 6.2.4 Intensity Scaling 171 6.2.5 Masking 173 6.3 Colour Image Processing 175 6.3.1 False Colouring 175 6.3.2 Colour Space Conversion 176 6.3.3 Colour Thresholding 192 6.3.4 Colour Correction 193 6.3.5 Colour Enhancement 197 6.4 Summary 197 7 Histogram Operations 199 7.1 Greyscale Histogram 199 7.1.1 Data Gathering 201 7.1.2 Histogram Equalisation 206 7.1.3 Automatic Exposure 210 7.1.4 Threshold Selection 211 7.1.5 Histogram Similarity 219 7.2 Multidimensional Histograms 219 7.2.1 Triangular Arrays 220 7.2.2 Multidimensional Statistics 222 7.2.3 Colour Segmentation 226 7.2.4 Colour Indexing 229 7.2.5 Texture Analysis 231 Contents vii 8 Local Filters 233 8.1 Caching 233 8.2 Linear Filters 239 8.2.1 Noise Smoothing 239 8.2.2 Edge Detection 241 8.2.3 Edge Enhancement 243 8.2.4 Linear Filter Techniques 243 8.3 Nonlinear Filters 248 8.3.1 Edge Orientation 250 8.3.2 Non-maximal Suppression 251 8.3.3 Zero-Crossing Detection 252 8.4 Rank Filters 252 8.4.1 Rank Filter Sorting Networks 255 8.4.2 Adaptive Histogram Equalisation 260 8.5 Colour Filters 261 8.6 Morphological Filters 264 8.6.1 Binary Morphology 264 8.6.2 Greyscale Morphology 269 8.6.3 Colour Morphology 270 8.7 Adaptive Thresholding 271 8.7.1 Error Diffusion 271 8.8 Summary 273 9 Geometric Transformations 275 9.1 Forward Mapping 276 9.1.1 Separable Mapping 277 9.2 Reverse Mapping 282 9.3 Interpolation 285 9.3.1 Bilinear Interpolation 286 9.3.2 Bicubic Interpolation 288 9.3.3 Splines 290 9.3.4 Interpolating Compressed Data 292 9.4 Mapping Optimisations 292 9.5 Image Registration 294 9.5.1 Feature-Based Methods 295 9.5.2 Area-Based Methods 299 9.5.3 Applications 305 10 Linear Transforms 309 10.1 Fourier Transform 310 10.1.1 Fast Fourier Transform 311 10.1.2 Filtering 318 10.1.3 Inverse Filtering 320 10.1.4 Interpolation 321 10.1.5 Registration 322 viii Contents 10.1.6 Feature Extraction 323 10.1.7 Goertzel’s Algorithm 324 10.2 Discrete Cosine Transform 325 10.3 Wavelet Transform 328 10.3.1 Filter Implementations 330 10.3.2 Applications of the Wavelet Transform 335 10.4 Image and Video Coding 336 11 Blob Detection and Labelling 343 11.1 Bounding Box 343 11.2 Run-Length Coding 346 11.3 Chain Coding 347 11.3.1 Sequential Implementation 347 11.3.2 Single Pass Algorithms 348 11.3.3 Feature Extraction 350 11.4 Connected Component Labelling 352 11.4.1 Random Access Algorithms 353 11.4.2 Multiple-Pass Algorithms 353 11.4.3 Two-Pass Algorithms 354 11.4.4 Single-Pass Algorithms 356 11.4.5 Multiple Input Labels 358 11.4.6 Further Optimisations 358 11.5 Distance Transform 359 11.5.1 Morphological Approaches 360 11.5.2 Chamfer Distance 360 11.5.3 Separable Transform 362 11.5.4 Applications 365 11.5.5 Geodesic Distance Transform 365 11.6 Watershed Transform 366 11.6.1 Flow Algorithms 366 11.6.2 Immersion Algorithms 367 11.6.3 Applications 369 11.7 Hough Transform 370 11.7.1 Line Hough Transform 371 11.7.2 Circle Hough Transform 373 11.7.3 Generalised Hough Transform 374 11.8 Summary 375 12 Interfacing 377 12.1 Camera Input 378 12.1.1 Camera Interface Standards 378 12.1.2 Deinterlacing 383 12.1.3 Global and Rolling Shutter Correction 384 12.1.4 Bayer Pattern Processing 384 Contents ix 12.2 Display Output 387 12.2.1 Display Driver 387 12.2.2 Display Content 390 12.3 Serial Communication 393 12.3.1 PS2 Interface 393 12.3.2 I2C 395 12.3.3 SPI 397 12.3.4 RS-232 397 12.3.5 USB 398 12.3.6 Ethernet 398 12.3.7 PCI Express 399 12.4 Memory 400 12.4.1 Static RAM 400 12.4.2 Dynamic RAM 401 12.4.3 Flash Memory 402 12.5 Summary 402 13 Testing, Tuning and Debugging 405 13.1 Design 405 13.1.1 Random Noise Sources 406 13.2 Implementation 409 13.2.1 Common Implementation Bugs 410 13.3 Tuning 412 13.4 Timing Closure 412 14 Example Applications 415 14.1 Coloured Region Tracking 415 14.2 Lens Distortion Correction 418 14.2.1 Characterising the Distortion 419 14.2.2 Correcting the Distortion 421 14.3 Foveal Sensor 424 14.3.1 Foveal Mapping 425 14.3.2 Using the Sensor 429 14.4 Range Imaging 429 14.4.1 Extending the Unambiguous Range 431 14.5 Real-Time Produce Grading 433 14.5.1 Software Algorithm 434 14.5.2 Hardware Implementation 436 14.6 Summary 439 References 441 Index 475 x Content

FPGA图像处理入门代码 灰度直方图的verilog实现

这是本人自己编写的可用于256*256大小的图像进行sobel边缘检测的vhd文件，可在QuartusII或MaxplisII下综合和仿真，并在FPGA上测试过。可以进行修改支持其他大小图像的sobel边缘检测，同时还可以实现其它的图像模块化处理算法，例如高斯滤波，平滑等。