matlab图像去模糊算法代码

读取单幅envi图像格式的img图像，并将其显示出来(read img)

有关彩色图像分割与复杂场景下目标跟踪方法研究的一篇博士论文(On the color image segmentation and complexity of the scene target tracking methods under study for a Ph D thesis)

计算局部形状描述符梯度方向直方图（HOG），直接输入图像即可用。(Calculate the local shape descriptors gradient orientation histogram (HOG), the input image can be used directly.)

离散分数阶傅立叶变换，算法参考 C. Candan, M.A. Kutay, and H.M. Ozaktas. The discrete Fractional Fourier Transform. IEEE Trans. Sig. Proc., 48:1329--1337, 2000 (Discrete fractional Fourier transform algorithm reference C. Candan, MA Kutay, and HM Ozaktas. The discrete Fractional Fourier Transform. IEEE Trans. Sig. Proc., 48:1329- 1337, 2000)

用小波变换进行图像增强，先对原始图像进行非下采样的小波分解，在对每一层的高频分解系数进行处理，得到变换后的小波系数，再进行小波重构。(Image enhancement using wavelet transform, the original image and non-sampling wavelet decomposition in the high frequency decomposition coefficients of each layer, get the wavelet coefficients after the transformation, then the wavelet reconstruction. )

说明：  使用MATLAB生成二维voronoi图的代码，可以用作后续二维voronoi的多晶模型建立(The code of two-dimensional Voronoi diagram generated by MATLAB can be used to build the polycrystalline model of two-dimensional voronoi.)

斑点噪声的去除方法，主要适用sar图像，比较适合开题使用(Speckle noise removal methods, mainly for sar image, more suitable for the use of open questions)

说明：  将girl 图像进行分割，达到2*4的图像分割结果。并使用tight_subplot函数将分割间距变小。(The girl image is segmented to achieve a 2*4 image segmentation result. And use the tight_subplot function to make the division interval smaller.)

针对多聚焦图像融合，本文首先介绍了小波变换融合算法，虽然小波变换方法无冗余，高频分量损失较小，具有较好的融合效果，但存在两个主要缺点：一是移变性，二是融合图像在重构时会受到一些外来因素的影响，所以仍会丢失一些边缘信息，为了克服小波变换法的以上缺点，可以采用基于小波分解和点扩展函数模型PSF相结合的融合方法。该方法首先对不同的图像进行无降2采样的小波分解，以保持与源图像大小相同，然后分别将其各方向、各尺度的高频分量进行叠加，并依此提取其高频分量的特征信息来判定清晰目标或模糊目标，以此来设计融合算法，采用一定的策略将两副源图像进行融合，从而避开了小波的反变换，因此融合后的图像具有比小波变换法更好的融合效果。(multi-focus image fusion, this paper introduces the wavelet transform algorithm, Although the wavelet transform non-redundant, the loss of high-frequency components are smaller, better integration effect, But there are two major drawbacks : First, the shift variability and the second is the integration of image reconstruction will be subject to a number of external factors. Therefore, there would still be some marginal loss of information, in order to overcome the wavelet transform of the above shortcomings, can be used based on wavelet decomposition and the point spread function PSF model combining the fusion method. The first pair of different images ratchet two sampling wavelet decomposition, and to maintain the same source image size. Then all of its direction, the scale of high-freque)

多传感器多目标跟踪技术研究，，主要研究多传感器多目标跟踪技术 (Multi-sensor multi-target tracking technology research, mainly multi-sensor multi-target tracking technology)