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Description: 可讀可貼bitmap，也有使用者定義的透明參數可修改-drawing code that would draw images, either bitmaps or icons, either normally or transparently, grey-scaled or disabled, possibly stretched or at least centered on the button
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Size: 7168 |
Author: kurumi |
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Description: QPSK modulation with Grey Codding
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Size: 2048 |
Author: bobo |
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Description: 对原始图像进行球面投影,内含两幅原始图像,可以对彩色或灰度图像进行投影,绝对能用-Spherical projection to an orginal image,including color and grey image,absolutely useful
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Size: 463872 |
Author: bixuehe |
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Description: 并行计算程序
Description: This program blurs an image file in a parallelized computation
The root process reads the file and distributes a part of the image file to
other processes. Each process makes the filter operation on the part of the image data which is received from the root. Then all the processes send their blurred image data to the root and root writes the result in a file-Distributed Image Processing Filter
Write a program that blurs an image file in a parallelized computation. Whenever possible, use collective
operations (MPI_Scatter, MPI_Gather). The root process reads the image file from the NFS
server, distributes the data of the file among all processes, and gathers the results into the output file.
Each processor should receive a part of the image only. The image file is provided as a raw image file.
It can be read using the C function fread() with a single call and written with the single call of the
function fwrite(). The image is given as an array of h rows, a row has 1280 pixels , where each pixel
is one unsigned char grey value. You may assume that h is lower than or equal to 8192.
a) Write an MPI program in which the root process prepairs the data, so that all other processes
get their data by exactly one MPI_Scatter operation.
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Size: 2048 |
Author: 刘铭 |
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Description: 用脉冲耦合神经网络作图像处理，当输入为灰度图像或彩色图像时，该方法能产生一系列脉冲图像-PCNN is a neural network algorithm that produces a series of binary pulse images when stimulated with a grey scale or colour image
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Size: 4689920 |
Author: 陈财明 |
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Description: A program to demonstrate the optimization process of ant colony optimization for the traveling saleman problem (TSP). The cities are shown as red circles, the pheromone on the connections between them (fully connected graph) by gray lines. The darker the grey, the more pheromone is currently on the edge. During the optimization, the currently best found tour is drawn in red. To run the optimization, first create a random TSP, then create an ant colony, and finally run the optimization.
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Size: 20480 |
Author: hjp |
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Description: Application of Grey System Theory on Biology: (2) Photosystem I
Attributes More Than Photosystem II to Photosynthesis Rate in Higher
Plants
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Size: 33792 |
Author: Pak Su Jong |
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Description: LABVIEW图像获取及分割处理，需NI图像卡及普通摄像头，也可修改为静态图像处理。-LABVIEW image acquisition and segmentation processing, graphics card and the required NI ordinary camera can also be modified as a static image processing.
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Size: 25600 |
Author: 尹名航 |
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Description: VB.NET 1.1 图像处理 Class 灰度、锐化、拉伸、模糊、切割图片、旋转图片。-VB.NET 1.1 image processing Class grayscale, sharpening, stretching, fuzzy, cutting pictures, rotate the picture.
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Size: 2048 |
Author: 甘意扬 |
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Description: 1.对一个256*256的图像进行DCT变换得到图像D，将D得斜下角数值置为零，然后进行DCT反变换.
2.对源图像进行K-L转换
1和2比较-1.Get a grey level image which size is N*N. (For example, 256*256, however,
N = ), and partition to 8*8 sub images.
2.. Apply DCT to these sub images, and get the transformed image D with DCT
coefficients for elements.
3. From D, keep the coefficient values for only upper left triangular region and set
zeros for lower right region to approximate the image. (That is, only half of data
is used.)
4.Take Inverse DCT to get the approximated image.
2 . Get the covariance matrix of image.
3 . Calculate the corresponding eigenvectors and eigenvalues.
4 . Represent the original image with Singular Value Decomposition.
5 . Approximate the image by taking off the 4 smallest eigenvalues. (That is, only
half of information is used.)
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Size: 1024 |
Author: zhengyan |
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Description: 把一个256*256的图像分成8*8小块，然后进行DFT变换，分别比较在空间域和频域内对图像进行二次抽样和差值最后得出的图像比较-1. Get a grey level image which size is N*N. (For example, 256*256, however,
N = ), and partition to 8*8 sub images.
2. Apply DFT to these sub images, and get the fourier transformed image F.
3. Derive the proper subsampling function matrix S in spatial domain.
4. Multiplying proper 4*4 DFT matrix T to matrix S, derive the frequency version
of subsampling function matrix, S.
5. Similarly, derive the frequency version of interpolation matrix, I.
6. Apply these matrices to each sub image of F (which is DFT of original image),
and get the final image, taking inverse DFT.
7. Apply subsampling/interpolation function matrix S/I to original image in spatial
domain and get the final image.
8. Compare the results from 6, 7.
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Size: 2048 |
Author: zhengyan |
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Description: 将一幅256*256的图像分成8*8的小块，对其进行DFT变换。分别比较在空间域和频域内对源图像进行二次抽样和差值最后比较不同-1. Get a grey level image which size is N*N. (For example, 256*256, however,
N = ), and partition to 8*8 sub images.
2. Apply DFT to these sub images, and get the fourier transformed image F.
3. Derive the proper subsampling function matrix S in spatial domain.
4. Multiplying proper 4*4 DFT matrix T to matrix S, derive the frequency version
of subsampling function matrix, S.
5. Similarly, derive the frequency version of interpolation matrix, I.
6. Apply these matrices to each sub image of F (which is DFT of original image),
and get the final image, taking inverse DFT.
7. Apply subsampling/interpolation function matrix S/I to original image in spatial
domain and get the final image.
8. Compare the results from 6, 7.
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Size: 2048 |
Author: zhengyan |
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Description: 这个是C制作的源代码。。。
对一幅图像进行DFT变换，分别对源图像在空间域和频域里进行二次抽样和差值，最后得出结果比较。- Get a grey level image which size is N*N. (For example, 256*256, however,
N = ), and partition to 8*8 sub images.
Apply DFT to these sub images, and get the fourier transformed image F.
3. Derive the proper subsampling function matrix S in spatial domain.
4. Multiplying proper 4*4 DFT matrix T to matrix S, derive the frequency version
of subsampling function matrix, S.
5. Similarly, derive the frequency version of interpolation matrix, I.
6. Apply these matrices to each sub image of F (which is DFT of original image),
and get the final image, taking inverse DFT.
7. Apply subsampling/interpolation function matrix S/I to original image in spatial
domain and get the final image.
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Size: 2048 |
Author: zhengyan |
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Description: 一个空间点P绕一个中心点C旋转可用接续的三个变换来实现：第1个变换平移点C到坐标系原点位置，第2个变换将点P绕原点旋转，第3个变换平移点C回到其相对于坐标系原点的原始位置。当原始图像点乘以变换矩阵，得到新的图像位置点时，其位置可能不是整数值，该位置的灰度值需要通过灰度插值获得。在不改变输出图像大小的情况下，超出原始图片范围的区域，MATLAB原有函数imrotate的处理方法为将其灰度值全部置零，本文通过取模操作对超出区域进行了另外一种控制方法imrotate_my函数，能够较好的显示出图像旋转的边界变化。
-A space around the center point P C available in three rotating to realize the transformation: the first one translation: C to coordinate transformation, the origin place of 2 transform point P around the rotation, the origin of the three points to the transformation of C translation relative to the original position of axis. When the original image point multiply the transformation matrix, a new image position, the position may not integer, this position gray value by gray interpolation gain needed. No change in the size of the image output circumstance, the area beyond the original image, the original function imrotate MATLAB treatment method for the grey value all zeros, based on beyond the area take mould operation on another control method imrotate_my function, to better show of image rotation boundaries.
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Size: 2048 |
Author: 肥猪流 |
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Description: gm（1，1）灰色预测源码，敬请查看，如有问题请联系-grey model，based on c++，please
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Size: 1024 |
Author: wenxia |
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Description: Implementation of a Max Lloyd quantizer using matlab for grey scale images. The quantizer uses random starting conditions and find the locally optimal quantizer levels.
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Size: 1024 |
Author: bob |
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Description: Recognition of visual patterns and characters are independent of position, size, and orientation in the visual field has been the goal of much recent research. The method presented in this paper meets all these condition. An off-line signature matching system which is based on Hu moment invariant method is presented here. Signature matching uses a four - steps process. In first step the scanned or captured color images are initially converted to grey scale. Second step performs normalization and digitization of the original signature. Noise reduction (also called “smoothing” or “noise filtering”) is one of the most important processes in image processing is performed in third step and then moment invariant vectors are obtained in the last step. Signature matching system is implemented using MATLAB and ability of the system can be increased by using additional features in the input data set.
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Size: 8192 |
Author: shivshankar mishra |
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Description: VC++6.0图像点运算图像反色图像对比度灰度拉伸等变换 适合8位的灰度图像-code VC picture LineTrans contrast stretch for 8bit grey picture
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Size: 560128 |
Author: Johnson |
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Description: GRAY LEVEL grey level co-occurrence matrix
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Size: 63488 |
Author: Sekar |
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Description: The following codes a)convert an 8-grey scale image to a binary. b) convert a 24-bit colour image to its red channel image c)convert an 8-bit colour image to a grey-scale iamge.
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Size: 1985536 |
Author: seduex |
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