SNLSDP-0

Today, there is almost no area of technical endeavor that is not impacted in some way by digital image processing.We can cover only a few of these applications in the context and space of the current discussion. However, limited as it is, the material presented in this section will leave no doubt in the reader’s mind regarding the breadth and importance of digital image processing.We show in this section numerous areas of application, each of which routinely utilizes the digital image processing techniques developed in the following chapters. Many of the images shown in this section are used later in one or more of the examples given in the book. All images shown are digital.

compressive sensing theory

峰值滤波用于数据特征处理，可提高算法运算速度和鲁棒性(Peak filter characteristics for data processing, the operation speed can be increased and the robustness of the algorithm)

ihsantest3 matlab code

光度立体成像 通过物体在两个不同点光源下拍摄的两张图片 获得物体的三维信息(Photometric stereo imaging computer vision)

图像截取（MATLAB）,用MATLAB代码编写的程序，还是挺有用的(img_introp)

matlab implementation of wimax downlink

无线传感器网络里的定位经典dvhop算法实现(Wireless sensor networks where the positioning of dvhop Algorithm)

一种基于红外图像分层处理及动态压缩的 DDE 算法。该算法先将原始14bits 红外图像数据信息中的大动态低频背景和小动态高频细节进行分离提取，并分别对提取的细节层和背景层进行相应的灰度增强和灰度抑制处理，再调整和压缩各图层的动态范围并最终合成 8bits图 像。实验结果表明，该算法能较好地保留并突出原始红外图像中的边缘和细节信息，达到了预期设计的目标。 (put forward a DDE algorithm based on hierarchical processing and dynamic compression of infrared image． At first，this algorithm dissociates the background ( with wide dynamic and low frequency) and the detail ( with narrow dynamic and high frequency) in the data information ( 14 bits) of original infrared image，and pick up them respectively． Then，it enhances the gray of details layer and restrains the gray of background layer，and readjusts and compresses dynamic range of each layer． Finally，it composites output image ( 8 bits) ． The experimental results show that the proposed algorithm can retain detail information and edges in original infrared image and carry the purpose of design． )

一个圆周卷积的代码~调用形式为y=juanji(h,x1,M) 其中，h和x1为输入，h为滤波器系数，x1为输入采样信号，输出为y,M为输入信号x1的长度。(A circular convolution of the code to call the form of y = juanji (h, x1, M) of them, h, and x1 for the input, h for the filter coefficient, x1 sampling input signals, output y, M for the input signal x1 length.)