区域编码和阈值编码实现图像压缩

CVPR2013中出现的一种显著性特征检测算法，该算法用于模拟人眼视觉识别过程，提取图像中的显著性特征借后期目标对象的检测跟踪等使用，该算法(Context-Aware Saliency Detection。matlab implementation of an classical saliency detection alrogithm,which imitate our recognition process of eyes)

圆形图表的处理，包括大圆套小圆，双指针，针对设计仪表的初学者很有帮助(Treatment of circular charts, including the great circle sets of small round, double pointer, very helpful for beginners instrument design)

粗化细化程序很好用的，大家试市啊，(crude refining procedures of the good, we take the city ah,!)

db4小波的提升小波分解，从已发表的论文中得来，可放心使用(db4 wavelet lifting wavelet decomposition, the published papers come, you can be assured)

提出一种基于特征点的运动场景图像拼接算法。基于相似变换消除选取在运动物体上的特征点，并使用RANSAC算法进行外点的剔除。在融合阶段，根据齐次变换矩阵求得对2幅图像的差异图像，并执行区域增长算法。从而分割出运动区域。使用一种分段映射算法生成全景图像。实验证明了算法的有效性。(A feature-based algorithm for image mosaics of 8c宅Iles with moving objects is pI．oposcd．The algorithm eliminates the feature points which arc selected in moving objects using similarity transform，and the outliers are eliminated using RANSAC algorithm．In the image blend phase，a difference of two images is created using homogeneous transformation matrix，and a region growth algorithm is implemented SO as to segment the movmg object region．A piecewise mapping algorithm for generating panoramic images is used．Experimental results show the effectiveness of the algorithm．)

说明：  该文件可以读取MRI raw data，磁共振指的是自旋磁共振（spin magnetic resonance）现象。其意义上较广，包含核磁共振(nuclear magnetic resonance, NMR)、电子顺磁共振（electron paramagnetic resonance, EPR）或称电子自旋共振（electron spin resonance, ESR）(The file can read MRI raw data, Magnetic resonance refers to the phenomenon of spin magnetic resonance. It is broader in meaning and includes nuclear magnetic resonance (NMR), electron paramagnetic resonance (EPR) or electron spin resonance (ESR))

A Low Complexity Motion Compensated Frame Interpolation Method

最大最小距离 聚类算法，可以对一维或者二维信号进行聚类分析。尤其是两类化情况较好时。(maxmum and minimum Cluster Algorithm)

说明：  使用matlab编写的源程序 高斯噪声产生的源代码(prepared by the use of Matlab source Gaussian noise source)

对遥感图像进行无监督分类，形成决策树，实现地物的标定(Unsupervised classification of remote sensing images to form a decision tree, the calibration of surface features)