图像处理大作业.zip
本文件包含图像处理的相关实验，包括小波变换的图像去噪和边缘特征提取实现，全局、局部直方图均衡化的实现，PSNR、SSMR图像指标的计算；同态滤波的实现。所有MATLAB代码均为自己编码实现，不调用现有MATLAB库函数。包含理论的讲解和代码的具体实现，代码详细注释。
文件下载
资源详情
[{"title":"（ 60 个子文件 13.34MB ） 图像处理大作业.zip","children":[{"title":"图像大作业","children":[{"title":"图像处理大作业_报告.docx <span style='color:#111;'> 4.42MB </span>","children":null,"spread":false},{"title":"实验中MATLAB源代码介绍.txt <span style='color:#111;'> 684B </span>","children":null,"spread":false},{"title":"图像处理大作业_报告.pdf <span style='color:#111;'> 1.49MB </span>","children":null,"spread":false},{"title":"伪代码","children":[{"title":"图像直方统计图.png <span style='color:#111;'> 69.41KB </span>","children":null,"spread":false},{"title":"局部均衡化.png <span style='color:#111;'> 127.31KB </span>","children":null,"spread":false},{"title":"PSNR.png <span style='color:#111;'> 86.33KB </span>","children":null,"spread":false},{"title":"同态滤波.png <span style='color:#111;'> 86.09KB </span>","children":null,"spread":false},{"title":"SSIM.png <span style='color:#111;'> 74.53KB </span>","children":null,"spread":false},{"title":"均衡化.png <span style='color:#111;'> 84.88KB </span>","children":null,"spread":false},{"title":"硬阈值处理.png <span style='color:#111;'> 94.15KB </span>","children":null,"spread":false}],"spread":true},{"title":"图像处理大作业_源代码+中间输出结果","children":[{"title":"Project 2","children":[{"title":"My_Histogram.m <span style='color:#111;'> 2.04KB </span>","children":null,"spread":false},{"title":"实验输出","children":[{"title":"局部_Gray2.4.png <span style='color:#111;'> 3.07KB </span>","children":null,"spread":false},{"title":"局部_Gray1.1—图 2.1.4-1.1.png <span style='color:#111;'> 166.69KB </span>","children":null,"spread":false},{"title":"去噪后均衡化_3_参数.jpg <span style='color:#111;'> 10.07KB </span>","children":null,"spread":false},{"title":"局部_Gray1.4.png <span style='color:#111;'> 3.09KB </span>","children":null,"spread":false},{"title":"去噪后均衡化_3—图2.1.5-3.jpg <span style='color:#111;'> 107.35KB </span>","children":null,"spread":false},{"title":"局部_Gray3.4.png <span style='color:#111;'> 3.00KB </span>","children":null,"spread":false},{"title":"去噪后均衡化_1_参数.jpg <span style='color:#111;'> 10.57KB </span>","children":null,"spread":false},{"title":"局部_Gray2.3—图 2.1.4-2.2.png <span style='color:#111;'> 13.01KB </span>","children":null,"spread":false},{"title":"局部_Gray3.3—图 2.1.4-3.2.png <span style='color:#111;'> 11.35KB </span>","children":null,"spread":false},{"title":"局部_Gray2.2—图 2.1.4-2.1.png <span style='color:#111;'> 2.59MB </span>","children":null,"spread":false},{"title":"去噪后均衡化_2—图 2.1.5-2.jpg <span style='color:#111;'> 36.81KB </span>","children":null,"spread":false},{"title":"局部_Gray3.1—图 2.1.4-3.1.png <span style='color:#111;'> 524.91KB </span>","children":null,"spread":false},{"title":"局部_Gray2.1—图 2.1.4-2.1.png <span style='color:#111;'> 1.39MB </span>","children":null,"spread":false},{"title":"去噪后均衡化_1—图 2.1.5-1.jpg <span style='color:#111;'> 22.63KB </span>","children":null,"spread":false},{"title":"全局直方图均衡化2—图2.1.3-2.png <span style='color:#111;'> 58.04KB </span>","children":null,"spread":false},{"title":"局部_Gray3.2—图 2.1.4-3.1.png <span style='color:#111;'> 1.42MB </span>","children":null,"spread":false},{"title":"全局直方图均衡化1—图2.1.3-1.png <span style='color:#111;'> 74.94KB </span>","children":null,"spread":false},{"title":"去噪后均衡化_2_参数.jpg <span style='color:#111;'> 10.93KB </span>","children":null,"spread":false},{"title":"全局直方图均衡化3—图2.1.3-3.png <span style='color:#111;'> 43.04KB </span>","children":null,"spread":false},{"title":"局部_Gray1.3—图 2.1.4-1.2.png <span style='color:#111;'> 13.50KB </span>","children":null,"spread":false},{"title":"局部_Gray1.2—图 2.1.4-1.1.png <span style='color:#111;'> 309.97KB </span>","children":null,"spread":false}],"spread":false},{"title":"PSNR.m <span style='color:#111;'> 255B </span>","children":null,"spread":false},{"title":"My_Histogram_section.m <span style='color:#111;'> 2.21KB </span>","children":null,"spread":false},{"title":"My_imhist.m <span style='color:#111;'> 394B </span>","children":null,"spread":false},{"title":"SSIM.m <span style='color:#111;'> 1.16KB </span>","children":null,"spread":false}],"spread":true},{"title":"Project 1","children":[{"title":"My_Dnoise_wavelet.m <span style='color:#111;'> 477B </span>","children":null,"spread":false},{"title":"实验输出","children":[{"title":"小波去噪_sym1_2—图1.1.4-2.jpg <span style='color:#111;'> 115.67KB </span>","children":null,"spread":false},{"title":"image2_去噪_边缘提取—图1.2.4-2.jpg <span style='color:#111;'> 54.22KB </span>","children":null,"spread":false},{"title":"小波去噪_不同层级数比较_1—图1.1.4-3.jpg <span style='color:#111;'> 65.01KB </span>","children":null,"spread":false},{"title":"小波去噪_不同层级数比较_2—图1.1.4-4.jpg <span style='color:#111;'> 131.16KB </span>","children":null,"spread":false},{"title":"image2_去噪_边缘提取—提取流程.jpg <span style='color:#111;'> 204.84KB </span>","children":null,"spread":false},{"title":"image1_去噪_边缘提取—提取流程.jpg <span style='color:#111;'> 129.71KB </span>","children":null,"spread":false},{"title":"image1_去噪_边缘提取—图1.2.4-1.jpg <span style='color:#111;'> 41.88KB </span>","children":null,"spread":false},{"title":"小波去噪_sym1_1—图1.1.4-1.jpg <span style='color:#111;'> 81.16KB </span>","children":null,"spread":false},{"title":"小波去噪_db1_2—图1.1.3-2.jpg <span style='color:#111;'> 115.67KB </span>","children":null,"spread":false},{"title":"小波去噪_db1_1—图1.1.3-1.jpg <span style='color:#111;'> 81.16KB </span>","children":null,"spread":false}],"spread":true},{"title":"myfun_3.m <span style='color:#111;'> 2.96KB </span>","children":null,"spread":false},{"title":"myfun.m <span style='color:#111;'> 658B </span>","children":null,"spread":false},{"title":"image2.jpg <span style='color:#111;'> 186.43KB </span>","children":null,"spread":false},{"title":"image1_去噪.jpg <span style='color:#111;'> 76.67KB </span>","children":null,"spread":false},{"title":"My_Dnoise_wavelet_dlayers.m <span style='color:#111;'> 500B </span>","children":null,"spread":false},{"title":"wavelet_edge_detection.m <span style='color:#111;'> 1.58KB </span>","children":null,"spread":false},{"title":"image2_去噪.jpg <span style='color:#111;'> 129.49KB </span>","children":null,"spread":false},{"title":"image1.jpg <span style='color:#111;'> 169.45KB </span>","children":null,"spread":false},{"title":"myfun_2.m <span style='color:#111;'> 1.96KB </span>","children":null,"spread":false}],"spread":false},{"title":"附加题","children":[{"title":"实验输出","children":[{"title":"同态滤波_1—图2.1.5-1.jpg <span style='color:#111;'> 24.02KB </span>","children":null,"spread":false},{"title":"同态滤波_2—图2.1.5-2.jpg <span style='color:#111;'> 34.58KB </span>","children":null,"spread":false},{"title":"同态滤波_3—图2.1.5-3.jpg <span style='color:#111;'> 30.06KB </span>","children":null,"spread":false}],"spread":true},{"title":"My_Homomorphic_filtering.m <span style='color:#111;'> 1.44KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}],"spread":true}],"spread":true}]
评论信息
其他资源
- Web网页设计——茶道
- XH2.54系列AD封装及3D
- 游戏设计梦工厂英文版（第三版）
- c#4参数和七参数的计算
- 系统架构设计师教程__杨春晖主编_北京 带书签功能
- 狂神docker笔记（超详细）.zip
- WEB方式直连大华设备Demo（带云台）&SDK;
- 电子技术基础+数字部分第六版+学习辅导与习题解答
- 附近商家多门店地图导航V1.6.1 开源版.rar
- MySql.Data.dll 5.2.3.0
- 倒Y-型原子系统中增益辅助的慢光研究
- qssdemo.zip
- OC Control MarginLabel(间距Label).zip
- linux图形库.txt
- 17个前端常用功能小实战1_CSS3引领页面动画新潮流，开发梦幻西游项目.wmv
- python基础6循环.pdf
- C++大型作业----公司员工管理系统
- mfc+opencv读取摄像头视频并实现抓图
- STM32F103中文教程及参考手册.pdf
- 数字电子技术基础答案(阎石.第五版).pdf
- apktool2.3.3.jar
- 贝塞尔函数
- hanlp1.7jar包下载
- sm4加解密_工具
免责申明
【只为小站】的资源来自网友分享，仅供学习研究，请务必在下载后24小时内给予删除，不得用于其他任何用途，否则后果自负。基于互联网的特殊性，【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查；无论 【只为小站】 经营者是否已进行审查，用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明
本站所有资源不代表本站的观点或立场，基于网友分享，根据中国法律《信息网络传播权保护条例》第二十二条之规定，若资源存在侵权或相关问题请联系本站客服人员，zhiweidada#qq.com，请把#换成@，本站将给予最大的支持与配合，做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明