camshift_matlab_ilekoaiq

利用contourlet变换、小波变换等方法，进行图像去噪，经过调试，完全可以运行，效果不错(Contourlet transform, wavelet transform methods for image denoising, debugging, can run, good results)

提取图像的局部二值特征；广泛用于纹理特征提取 具有旋转不变性(Extract local two value features of images; widely used in texture feature extraction. Rotation invariance)

说明：  基于各种算法的运动视频背景消除。使用opencv工具库，通过读取视频文件，处理视频，最后存储。(Background Subtract Algorithm)

说明：  当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。( This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio)

说明：  图像评估指标FSIM，传统全参考图像质量衡量标准FSIM（feature similarity），仿效SSIM的计算构成，同样由两部分耦合的幂指数，FSIM由PC项和GM项耦合(FSIM, the traditional full reference image quality measurement standard (FSIM), is composed of two parts of power index, FSIM is composed of PC term and GM term)

校正图像倾斜的程序，很好用，可以纠正几何投影变形(Image tilt correction procedures, very good use, you can correct the distortion geometric projection)

实现一个高精度指针仪表读数自动识别系统．用数码摄像头采集仪表的图像，然后利用数字图像处理技术识别刻度和指针，根据指针和刻度的相对位置计算指针读数值．使用条件霍夫变换（Constrained HOUGH Transfer）和中心投影分析法实现刻度的全自动识别，采用快速中心投影法进行指针检测与识别，识别速度达到68ms．实验结果表明该方法比传统方法速度快、精度高，系统读数平均误差仅为0．016％(To achieve a high precision automatic identification system pointer meter reading. Instrument with a digital camera capture images, then using digital image processing technology to identify scale and pointer, pointer and scale according to the relative position of the pointer readings calculated. Use Hough transform (Constrained HOUGH Transfer) and center projection analysis method to achieve scale automatic identification method using fast center projection target detection and recognition, recognition speed of 68ms. Experimental results show that faster than traditional methods, high accuracy, the system average error of only 0.016 of reading)

我改写后的graphbrian类，原本支持柱状图饼图和折线图的，现在添加了对这些图的风格调整，主要是增加了调整绘图区背景色和文本背景的功能，还增加了把图片保存为bmp文件的功能，以便用其他软件方便的打印。(I would then graphbrian category, which originally supported the pie chart histogram and line graph, and now added to adjust the style of these plans, the main adjustment is to increase the drawing area background color and text background function, but also an increase of the picture saved as bmp files, in order to use other software to facilitate printing.)

说明：  harris角点检测算法，用于图像拼接的配准(harris corner detection algorithm for image mosaic of the registration)

基于Matlab程序的图像细化算法基于Matlab程序的图像细化算法(Matlab program based on the image thinning algorithm based on image thinning algorithm Matlab program)