Design and Implementation of an Automatic Image Enhancement Algorithm Based on FPGAormalsize
-
摘要: 图像灰度分布不均匀是影响画质的重要因素,集中表现在对空间场景成像时,图像中存在大量过亮或过暗的区域.同时,算法的实时性和嵌入式平台的可实现性是设计实现空间应用载荷需要着重考虑的问题.针对上述问题,提出一种适合于FPGA实现的图像自动增强算法.算法以分段线性变换方法为基础,采用K均值聚类对视频图像的灰度直方图进行动态的区间划分;构建分段函数系数与直方图之间的定量关系,自动计算线性变换系数;采用高效的并行流水线结构设计,实现了基于FPGA的硬件处理系统.仿真和成像试验结果表明,该FPGA硬件系统实时性好,适应性强,针对不同的场景均取得较好的处理效果,具有广阔的应用前景.Abstract: Since there are many too dark or too bright areas in pictures that shot in the space, the corresponding images are uneven distributed, and the image quality is damaged. How to improve the processing speed of the algorithm and how to implement the algorithm by the embedded system are also key problems for space application. In this paper, the automatic image enhancement algorithm which is suitable to be implemented by the FPGA is proposed to solve these problems. The basis of the proposed algorithm is the piecewise linear transformation algorithm. In practical, firstly, the K-means clustering is used to segment the histogram into several sections automatically. Secondly, the quantitative relationship between the histogram distribution and the coefficients of the piecewise linear function is established. As a result, the coefficients can be automatically calculated. Thirdly, the corresponding FPGA system is implemented. And the high-performance parallel pipelined technology is used to ensure the real-time processing ability of the system. The simulations and the experimentations show that the proposed FPGA system is characterized as real-time processing ability and good adaptability. It can achieve good processing effects for different sceneries, and can be used in various practical applications.
-
Key words:
- Image enhancement /
- FPGA /
- Space remote sensing
-
[1] WANG Jun, LI Guohong. The application of CMOS image sensor in space remote sensing[J]. Spacecr. Recovery Remote Sens., 2008, 29(2):42-47(王军, 李国宏. CMOS图像传感器在航天遥感中的应用[J]. 航天返回与遥感, 2008, 29(2):42-47) [2] WANG Shoujue, DING Xinghao, LIAO Yinghao, et al. A novel bio-inspired algorithm for color image enhancement[J]. Acta Electron. Sin., 2008, 36(10):1970-1973(王守觉, 丁兴号, 廖英豪, 等. 一种新的仿生彩色图像增强方法[J]. 电子学报, 2008, 36(10):1970-1973) [3] CHENG H D, SHI X J. A simple and effective histogram equalization approach to image enhancement[J]. Digit Signal Proc., 2004, 14(2):158-170 [4] CAO Juliang, LÜ Haibao, LI Guanzhang. Histogram equalization algorithm based on adaptive local gray level modification[J]. Infrared Laser Eng., 2004, 33(5):513-515, 523(曹聚亮, 吕海宝, 李冠章. 基于自适应局部灰度修正的直方图均衡算法[J]. 红外与激光工程, 2004, 33(5):513-515, 523) [5] CHEN Mingliang, CHEN Chengxin, GU Jianping. Adaptive piecewise linear transform method based on histogram[J]. Foreign Electron. Meas. Technol., 2015, 34(2):36-38(陈明亮, 陈成新, 古建平. 一种基于直方图的自适应分段线性变换法[J]. 国外电子测量技术, 2015, 34(2):36-38) [6] LI Xiaobing. An adaptive piecewise linear gray scales transformation method for infrared measurement image[J]. Optoelectron. Technol., 2011, 31(4):236-239(李晓冰. 一种红外测量图像自适应分段线性灰度变换方法[J]. 光电子技术, 2011, 31(4):236-239) [7] ZHANG Junhua, YANG Gen, XU Qing. Image enhancement based on piecewise linear transformation[C]//The 14th National Conference on Image and Graphics. Fuzhou:China Society of Image and Graphics, 2008(张俊华, 杨根, 徐青. 基于分段线性变换的图像增强[C]//第十四届全国图象图形学学术会议论文集. 福州:中国图象图形学会, 2008) [8] ZHOU Yan, LI Qingwu, HUO Guanying. Adaptive image enhancement based on NSCT coefficient histogram matching[J]. Opt. Prec. Eng., 2014, 22(8):2214-2222(周妍, 李庆武, 霍冠英. 基于非下采样Contourlet变换系数直方图匹配的自适应图像增强[J]. 光学精密工程, 2014, 22(8):2214-2222) [9] ZHAO Yu. DR Image Enhancement Based on Weighted Red-black Wavelets Transform[D]. Guangzhou:Southern Medical University, 2015(赵雨. 基于加权红elax——elax黑小波变换的DR图像增强方法研究[D]. 广州:南方医科大学, 2015) [10] WANG Jianhua, LIU Chanlao, CHEN Dachuan, et al. Design of real-time video processing system based on DSP+FPGA[J]. Foreign Electron. Meas. Technol., 2007, 26(9):42-44(王建华, 刘缠牢, 陈大川, 等. 基于DSP+FPGA技术的实时视频采集系统的设计[J]. 国外电子测量技术, 2007, 26(9):42-44) [11] DIAZ J, ROS E, PELAYO F, et al. FPGA-based real-time optical-flow system[J]. IEEE Trans. Circuits Syst. Video Technol., 2006, 16(2):274-279 [12] GENOVESE M, NAPOLI E. ASIC and FPGA implementation of the gaussian mixture model algorithm for real-time segmentation of high definition video[J]. IEEE Trans. Very Large Scale Integr. Syst., 2013, 22(3):537-547 [13] YANG Huiling, WANG Jun, YANG Huiwei. Design of high frame frequency CMOS real-time image acquisition system[J]. Microcomput. Inf., 2008, 24(30):309-311(杨会玲, 王军, 杨会伟. 高帧频CMOS实时图像采集系统设计[J]. 微计算机信息, 2008, 24(30):309-311) [14] CHEN Biwei, LIANG Zhiyi, WANG Yanxin, et al. Design of a high speed CMOS imaging system based on FPGA[J]. Comput. Meas. Control, 2012, 20(5):1397-1400(陈必威, 梁志毅, 王延新, 等. 基于FPGA的高帧速CMOS成像系统设计[J]. 计算机测量与控制, 2012, 20(5):1397-1400) [15] MA Yitao, SHIBATA T. A binary-tree hierarchical multiple-chip architecture for real-time large-scale learning processor systems[J]. Jpn. J. Appl. Phys., 2010, 49(4S):04DE08 [16] CHEN Guozhu, LIU Tao, LI Yuanzong. Design of image sampling and storage system based on FPGA[J]. Mechan. Eng. Automat., 2007(4):44-46(陈国柱, 刘涛, 李元宗. 基于FPGA的图像采集与存储系统的设计[J]. 机械工程与自动化, 2007(4):44-46)
点击查看大图
计量
- 文章访问数: 1343
- HTML全文浏览量: 115
- PDF下载量: 696
- 被引次数: 0