gray

Retinex理论的基础理论是物体的颜色是由物体对长波（红色）、中波（绿色）、短波（蓝色）光线的反射能力来决定的，而不是由反射光强度的绝对值来决定的，物体的色彩不受光照非均匀性的影响，具有一致性，即retinex是以色感一致性（颜色恒常性）为基础的。不同于传统的线性、非线性的只能增强图像某一类特征的方法，Retinex可以在动态范围压缩、边缘增强和颜色恒常三个方面打到平衡，因此可以对各种不同类型的图像进行自适应的增强。(The basic theory of Retinex theory is the color of the object by object for the long wavelength (red), medium (green), short wave (blue) light reflection ability to decide, rather than by the intensity of reflected light of the absolute value to decide, the color of the object under illumination nonuniformity effects, consistent with the Retinex, that is based on color constancy (color constancy based). Different from the traditional linear, nonlinear image enhancement method of only one kind of features, Retinex can be in dynamic range compression, edge enhancement and three aspects of color constancy hit the balance, thus enhancing adaptive to a variety of different types of images can be.)

图像的平滑函数，对指定区域的图像，并有门限值和魔板大小限制。(the smooth of a bmp image)

数字图像处理，C语言，功能是打开一幅位图，实现几何变换。(Digital image processing, C language function is to open a bitmap, to achieve geometric transform.)

这是我的图形学的作业，实现光线跟踪。也是学别人做的，仅供学习用。(this is a study work about computer graphics , realizing tracking )

PAL制视频消隔行deinterlace的代码，共参考(PAL video system extinction deinterlace interlaced code, a total of reference)

文中主要研究使用普通的摄像头进行人眼视线方向的估计。在综合介绍了各种人眼视线检测方法的基础上提出了一种新的图像处理的方法来检测人眼视线方向(The main study used an ordinary camera line of sight of the human eye is estimated. In the consolidated a variety of the human eye sight detection method based on a new image processing method to detect the line of sight of the human eye)

说明：  给出了一种基于小波分形的图像有损压缩方法.首先，利用小波变换将图像分解为不同频率的分量，然后采用分形迭代函数系统、Huffman树等方法对它们进行编码.实验表明，该算法在保证还原图像质量的情况下，有较高的压缩比.(Image Compression Bassed on Wavelet and Fractal)

利用opencv+VC++实现对图像的边缘处理，从而对图像进行检测(Use opencv+ VC++ to achieve the edge of the image processing to the image detector)

经典的数字图像处理的形态学处理，包含源代码(Digital image processing morphological processing)

偏微分方程_PDEs_模型在图像处理中的若干应用(_PDEs_ Model partial differential equations in image processing)