资源列表
yasuoRGB
- 用小波基函数bior3.7完成对二维彩色图像的多分辨率分解，进而完成对图像信息的压缩-Using wavelet basis function bior3.7performed on a two-dimensional color Image multiresolution decomposition, and completion of image information compression
Spectrogram-with-RTDX-Using-MATLAB
- Spectrogram with RTDX Using MATLAB
weicaise
- 伪彩色处理增强视觉效果明显，是增强图像显示效果和提高视觉分辨率的一种常用的、最有效的手段。-Pseudo color processing to enhance the visual effect is obvious, is to enhance the image display effect and improve the visual resolution of a commonly used, the most effective means of.
watershed
- 分水岭分割方法，是一种基于拓扑理论的数学形态学的分割方法，其基本思想是把图像看作是测地学上的拓扑地貌，图像中每一点像素的灰度值表示该点的海拔高度，每一个局部极小值及其影响区域称为集水盆，而集水盆的边界则形成分水岭。-Watershed segmentation method, which is based on a topological theory of mathematical morphology segmentation method, the basic idea is that t
weiyena
- 对图像进行模糊处理，用逆滤波和维纳滤波恢复图像-The image fuzzy processing, with inverse filtering and wiener filtering image restoration
tetinex
- Retinex是由两个英文单词retina(视网膜)和cortex(皮层)组合而成，揭示了这一理论涉及模拟人类视觉系统的感知和理解过程。1963年Land首次提出了基于颜色恒常性的计算理论—— Retinex 理论，作为人类视觉对亮度和颜色感知的模型-Retinex is composed of two English words (retinal) and retina cortex (cortical) combination, reveals this theory to simulate
quzaosheng
- MATLAB多方法去高斯白噪声方法有：多幅图像平均、均值滤波、中值滤波-MATLAB more ways to gaussian white noise methods are: many images average, average filtering and median filtering
gaopinzengqiang
- MatLab理想低通滤波及高通滤波实现高频增强-MatLab ideal low pass filter high-pass filter and realize high frequency increased
bianma
- MATLAB通过DCT对图像进行区域编码以及门限编码压缩-MATLAB through the DCT to do image region code and threshold coding compression
caisezengqiang
- 与灰度图像相比，彩色图像不仅包括亮度信息，而且还有更多的有效信息，如色调、饱和度。实际上同样景物的灰度图像所包含的信息量与彩色图像难以相比，人类对色彩的感知更敏感，一幅质量较差的彩色图像似乎比一幅完美的灰度图像更具有吸引力。因此，对彩色图像分割方法的研究有利于克服传统灰度图像分割方式的不足，是一个更加广阔的研究领域-Compared with grey image, color image includes not only the brightness information, and mor
junhenghua
- 用matlab实现图像的直方图均衡化处理-Matlab image histogram equalization processing
dajingyudiedai
- 对阈值分割的研究结果表明，在像素分类错误率、被分区域均匀性等方面，大津法和迭代法性能较优-The threshold segmentation results indicate that, in the pixel classification error rate, divided region uniformity etc, Otsu method and iterative method has a better performance