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ImgComBasedonWavletandNN
- Matlab实现图像压缩与重构步骤 ① 对图像进行小波分解，得到第一层分解的低频系数和高频系数。 ② 保留低频系数，对高频系数进行基于神经网络的矢量量化编码，达到压缩。 ③ 根据码书以w还原高频系数 ④ 根据保留的低频系数和还原的高频系数重构图像 -Matlab realization image compression and the heavy construction step (1) pair of picture carries on the wavelet to
Imagesegementation
- To carry on small comparison for he different threshold value under the image segmentation result, have to use many windows,namely for take a look at a different threshold value of slice segmentation ’s result at same window , the window be divided i
1_embed
- DCT水印设I 为载体数据,W 为水印信号, K 为密钥,那 么嵌入水印后的载体Iw 可描述为[124 ] : Iw = F( I ,W , K) . (1) 式中, F 表示水印的嵌入策略。-I as a carrier of data, W for the watermark signal, K key, Then the watermark embedded vector can be described as Iw [124] : F = Iw (I, W, K). (1)
1_recover
- 设I 为载体数据,W 为水印信号, K 为密钥,那 么嵌入水印后的载体Iw 可描述为[124 ] : Iw = F( I ,W , K) . (1) 式中, F 表示水印的嵌入策略。-established as a carrier of data, W for the watermark signal, K key, Then the watermark embedded vector can be described as Iw [124] : F = Iw (I, W, K).
2_embed
- 设I 为载体数据,W 为水印信号, K 为密钥,那 么嵌入水印后的载体Iw 可描述为[124 ] : Iw = F( I ,W , K) . (1) 式中, F 表示水印的嵌入策略。-established as a carrier of data, W for the watermark signal, K key, Then the watermark embedded vector can be described as Iw [124] : F = Iw (I, W, K).
3_embed_recover
- 设I 为载体数据,W 为水印信号, K 为密钥,那 么嵌入水印后的载体Iw 可描述为[124 ] : Iw = F( I ,W , K) . (1) 式中, F 表示水印的嵌入策略。-established as a carrier of data, W for the watermark signal, K key, Then the watermark embedded vector can be described as Iw [124] : F = Iw (I, W, K).
improved_gaborfilter
- Bi-dimensional Gabor filter with DC component compensation This version of the 2D Gabor filter is basically a bi-dimensional Gaussian function centered at origin (0,0) with variance S modulated by a complex sinusoid with polar frequency (F,W) an
Motion-Compensated_Noise_Reduction_in_BW_Motion_Pi
- Motion-Compensated Noise Reduction in B&W Motion Picture Films,基于运动补偿的视频降噪，matlab实现，有完整文档说明-Motion-Compensated in B Noise Reduction
toolbox_signal
- This toolbox implements the algorithm in a fairly general way in a C file that can be called from Matlab. It allows to perform the traditional NL-means for denoising (for both B&W and color images) but also to use an arbitrary set of patches to perfo
MorphologicalThin
- 本代码实现了形态学细化。 特点：中间过程可以存储在输入中，因此节省存储空间；并且附有注解，便于理解；附有参考文献，有算法描述。This function implements the morphology thinning. Input pSrc is a float matrix in the range of [0, 1]. It supports in-place operation.Ref: Z. Guo and R. W. Hall, \"Parallel Thinning w
w
- 这是一篇关于立体视觉测量中的图像匹配策略研究的文章
exhaustive
- 穷尽 块匹配算法 motionsEstAnalysis.m scr ipt to execute all Algorithms motionEstES.m Exhaustive Search Algorithm costFuncMAD.m Mean Absolute Difference Function minCost.m minimum cost among macro blocks motionComp.m motion compensated image creato
PCA
- 主成分分析方法（PCA），PCA算法的理论依据是K-L变换，通过一定的性能目标来寻找线性变换W，实现对高维数据的降维。
nmf
- 基于非负矩阵分解（NMF）的人脸特征提取算法，NMF基本思想是找到一个线性子空间W，使的构成子空间的基本图像的像素点都是正值，而且人脸图像在子空间上的投影系数也是正数
zhongzhi
- 中值滤波代码！中值滤波是在1971年有J.W.Jwkey首先提并应用的在一维信号处理技术中(时间序列分析),后来被图像信号处理技术所引用.在一定的条件下,可以克服线性滤波器如最小均方滤波、平均值滤波等所带来的图像细节模糊，而且对滤波脉冲干扰及图像扫描噪声最为有效。特别适用在有很强的胡椒粉式或脉冲式的干扰时，因为这些干扰值与其邻近像素灰度有很大差异，因此经排序后取中值的结果是强迫将次干扰变成与其邻近的某些像素的灰度值一样，达到去除干扰的效果。在实际运算过程中并不需要图像的统计特性，这也是带来不少方
DigitalImageProcessing
- 图像处理中的图像变换的源码与变换后的结果图，包括dct变换，dft变换，w-h变换等
SR matlab
- W.T.Freeman 经典 基于例子的超分辨率重构matlab源码，图片自己可加，经测试可用-WTFreeman classic example of super-resolution reconstruction based on matlab source code, images themselves can be added, the test can be used
w-eag
- “Gradient based image transition region extraction and segmentation”（基于梯度的过渡区提取与分割）MatLAB 源码。-MatLAB code of “Gradient based image transition region extraction and segmentation”。
Fast_Lattice_Shape_Matching_2D_Demo
- 鲁邦实时形变的快速网格形状匹配方法，这个代码我是向作者要来的。-FastLSM: Fast Lattice Shape Matching for Robust Real-Time Deformation. This demo is intended to illustrate the kinds of behavior attainable using the FastLSM algorithm, and to provide an example implementation of
steerGaussmatlabcode
- 关于Steerable filtering decomposition 的matlab程序,- STEERGAUSS Implements a steerable Gaussian filter. This m-file can be used to evaluate the first directional derivative of an image, using the method outlined in: W. T. Freeman and E. H. Adelson