搜索资源列表
dark_channel_verify
- verify the idea of Single Image Haze removal Using Dark Channel prior, which is the best paper of CVPR in 2009 conference.
haze
- matlab代码实现的基于大气散射模型的去雾处理，有参考图片-processing matlab code based on the atmospheric scattering model to fog, the reference picture
matlab_lzy
- haze removal (cvpr09) matlab with face beautifulcation algorithmn
MATLAB图像与视频处理实用案例详解试读样章
- 详细讲解了25个MATLAB图像与视频处理实用案例（含可运行程序），涉及雾霾去噪、答题卡自动阅卷、肺部图像分割、小波数字水印、图像检索、人脸二维码识别、车牌定位及识别、霍夫曼图像压缩、手写数字识别、英文字符文本识别、眼前节组织提取、全景图像拼接、小波图像融合、基于语音识别的音频信号模拟灯控、路面裂缝检测识别、视频运动估计追踪、Simulink图像处理等多项重要技术(Explain in detail the 25 MATLAB image and video processing utility
A Fast Single Image Haze Removal Algorithm
- Single image haze removal has been a challenging problem due to its ill-posed nature. In this paper, we propose a simple but powerful color attenuation prior for haze removal from a single input hazy image. By creating a linear model for modeling
defog(matlab)
- MATLAB去雾程序，基于暗通道先验的图像去雾理论。可用于去雾霾实验。(MATLAB fogging program, based on the dark channel priori image demogging theory. It can be used to remove fog and haze test.)
Project_4_haze removal
- Source code haze removal with dark channel pririty
基于直方图优化的图像去雾技术matlab
- 展开雾霾天气的图象清晰化技术 的讨论，雾天图象的清晰化技术对其他 的恶劣天气的清晰化处理也有促进作用。(The technology of image sharpening in fog and haze is also discussed. The clarity of fog images can also help to clear the other bad weather.)
MATLAB雾霾交通标志shibie[GUI]
- 该课题为基于MATLAB bp神经网络的雾霾天气下交通标志的识别系统。主要分两步骤，一是进行图像去雾，采用暗通道的方法获取光透射率，从而去除雾霾。得到清晰的图片后，利用颜色的方法进行交通标志的定位，众所周知，交通标志基本是红，蓝，黄三色组成，根据RGB不同组合可以定位到不同颜色，因为存在误差，所以需要借助形态学相关知识，将得到的误干扰面积去除，从而实现精准定位。定位后，在原图基础上进行分割出彩色图标，利用bp神经网络方法，进行训练，识别，从而得出结果。本设计配有一个GUI可视化界面，操作简单容易