bilinear_zoom

说明：  Matlab边缘检测和区域生长图像分割算法代码，适合于图像边缘检测。(Matlab edge detection and region growing image segmentation algorithm code, suitable for edge detection.)

利用matlab实现数字图象处理的理想低通滤波器！！(Using matlab to achieve the desired low-pass filter! !)

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)

移频复调制ZOOMFFT能以指定的、足够高的采样频率分析频率轴上任一窄带内信号的频谱结构，在序列变换点数相同的情况下，ZOOMFFT能获得更高的频率分辨率(The frequency shift the complex modulation ZOOMFFT to specified former spectrum of the signal within a narrow band structure, a sufficiently high sampling frequency analysis of the frequency axis, in the case of the same sequence transform points, ZOOMFFT obtain a higher frequency resolution)

Simple Shape Detection using Hough Transform 用霍夫变换做为形状检测的matlab源码,从matlab官网下载(Simple Shape Detection using Hough Transform Hough transform used as a shape detection matlab source, from the official website download matlab)

详细设计了基于颜色直方图的图像检索 效果不错 计算速度快(Detailed design of the color histogram-based image retrieval good results fast calculation)

sift角点检测及匹配，在不同尺度空间下的角点检测方法，很方便实用。(sift corner detection and matching, the corner detection methods under different scales of space, it is convenient and practical.)

实现了基于关键像素点的FLICM图像分割算法，关键像素由局部最大值方法提取。(A FLICM image segmentation algorithm based on key pixels is implemented. Key pixels are extracted by local maximum method.)

说明：  经典的大津otsu算法在matlab中的实现程序，每一步都是经典步骤。(Otsu classical Otsus algorithm in matlab implementation process, each step is the classical steps.)

基于DCT的jsteg图像隐写及分析算法，MATLAB实现。 JSteg的算法主要思想是将秘密消息嵌入在量化后的DCT系数的最低比特位上，但对原始值为O、1的DCT系数不进行嵌入。提取秘密消息时，只需将载密图像中不等于0、l的量化DcT系数的LSB取出即可。(The main idea of the JSteg algorithm is to embed secret messages in the lowest bit of the quantized DCT coefficients, but the DCT coefficients of the original values are O and 1 are not embedded. When extracting secret messages, only the LSB of the quantized DCT coefficients not equal to 0 and l in the encrypted image can be taken out.)