Description: 提供了SAD算法和根据相关性检测算法，把图像分成四个块，根据每个块的相关性检测目标。-provided under the relevant algorithms and detection algorithm, the image is divided into four blocks, each block of target detection. Platform: |
Size: 18127 |
Author:爱玛 |
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Description: 分形用于图像压缩编码,分形编码非常费时，大部分时间浪费在给每个range块寻找合适的domain块，但如果减少搜索domain块的范围，编码速度将有很大提高。所以编码时用快限制分形编码,把图像分成4小块，每块中的range块只在这块中寻找domain块。-for fractal image compression coding, fractal coding is very time-consuming, most of the time wasted in each range block to find a suitable domain block, But if the search domain blocks to reduce the scope of coding speed will be greatly improved. So fast coding using fractal coding restrictions, the image is divided into four small pieces. every piece of the range block only find in this domain block. Platform: |
Size: 17575 |
Author:郭玉刚 |
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Description: 提供了SAD算法和根据相关性检测算法，把图像分成四个块，根据每个块的相关性检测目标。-provided under the relevant algorithms and detection algorithm, the image is divided into four blocks, each block of target detection. Platform: |
Size: 17408 |
Author:爱玛 |
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Description: 分形用于图像压缩编码,分形编码非常费时，大部分时间浪费在给每个range块寻找合适的domain块，但如果减少搜索domain块的范围，编码速度将有很大提高。所以编码时用快限制分形编码,把图像分成4小块，每块中的range块只在这块中寻找domain块。-for fractal image compression coding, fractal coding is very time-consuming, most of the time wasted in each range block to find a suitable domain block, But if the search domain blocks to reduce the scope of coding speed will be greatly improved. So fast coding using fractal coding restrictions, the image is divided into four small pieces. every piece of the range block only find in this domain block. Platform: |
Size: 17408 |
Author: |
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Description: 将一副256*256的灰度图像分成8*8的小图像块，然后进行dct变换-Will be a 256* 256 gray image is divided into 8* 8 small image blocks, and then proceed to DCT transform Platform: |
Size: 389120 |
Author:笨笨 |
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Description: 用的是局部颜色特征，再说细点是用里面的区域颜色直方图的方法。把图像归一化到256X256，把图像分成4X4块，计算16个区域的颜色直方图、、、
最后计算相似度是用欧氏距离.-Using local color feature, repeat fine-point is inside the regional color histogram method. The normalized image to 256X256, the image is divided into 4X4 blocks, the calculation of the 16 regional color histogram, calculated similarity is Euclidean distance. Platform: |
Size: 12361728 |
Author:周文 |
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Description: 为了提供较大的秘密信息嵌入量和保持良好的载密图像质量,依据人眼对变换剧烈及较暗区域均不敏感的视觉特点,提出了一种基于小波对比度和最低比特位替换(LSB)的图像密写方法.该方法先将载体图像分成固定大小的小块,对每一小块进行小波分解后计算小波对比度.然后,根据该块小波对比度绝对值之和确定该块可以嵌入的位平面层数.最后,采用LSB密写技术逐层嵌入秘密信息.实验结果表明,该密写方法能嵌入较多的信息和保持良好的载密图像质量,并且可直接从载密图像中提取秘密信息.-In order to provide larger capacity of the hidden secret data and to maintain a good visual quality of stego-image,in accordance with the visual property that human eyes are insensitive to edged area and dark area,a novel steganographic method based on wavelet contrast and Least-Significant-Bit(LSB)replacement is presented.First,an image is divided into blocks,and every block is decomposed into one-level wavelet to obtain the wavelet contrast.Then,the number of bit-plane embedded is decided with the s... Platform: |
Size: 263168 |
Author:boe |
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Description: 本文为图像分割源代码，把一幅在MATLAB中读入的图像分割成任意块-This article image segmentation source code, put a read into the MATLAB image is divided into arbitrary blocks Platform: |
Size: 104448 |
Author:刘永霞 |
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Description: 本文探讨了神经网络用于图像压缩的方法，提出了一种基于边缘信息检测的BP神经网络压缩方法:按图像各部分像素特征将图像分为平滑块、纹理块和边缘块，不同的分类块采用不同的隐含层数。实验结果证明本算法在在保证重建图像丰富细节的同时，能大大提高图像的压缩比。-This paper discusses the neural network for image compression method, edge information is presented based on BP neural network detection of compression method: According to the various parts of the image pixels will be characterized by a smooth image is divided into blocks, the texture blocks and edge blocks, different types of blocks implied different layers. Experimental results show that the algorithm in detail in ensuring the reconstruction of the image-rich at the same time, can greatly improve the image compression ratio. Platform: |
Size: 382976 |
Author:王蒙 |
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Description: 提出了一种新的基于离散小波变换(DWT)与奇异值分解(SVD)相结合的数字图像水印算法。该算法将原始图像作小波分解并将小波分解得到的低频子带进行分块，对每一块进行奇异值分解后，选取每块中最大的奇异值通过量化的方法嵌入经过Arnold置乱后水印信息。-A new wavelet transform based on discrete (DWT) and Singular Value Decomposition (SVD) combination of digital image watermarking algorithm. The algorithm for wavelet decomposition of the original image and wavelet decomposition low-frequency sub-band are divided into blocks, each a singular value decomposition, the selection of each block by the largest singular value methods to quantify Arnold scrambled after embedding the watermark . Platform: |
Size: 38912 |
Author:久久 |
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Description: 文中的方法是把图像分块，小波分解得到低频分量、高频分量，然后计算每一块的对比度，把图像块划分为清晰块、模糊块，把清晰块和模糊块相邻的区域定义为边界区域，融合时，直接选取清晰块作为融合后的相应块，对于边界区域，在小波分解的基础上采用基于对比度的像素选取的方法进行处理。-Paper, the method is to image segmentation, wavelet decomposition are low frequency, high frequency components, then calculate the contrast of each piece, the image block is divided into clear blocks, fuzzy block, to clear blocks and fuzzy block is defined as the border region adjacent to area, integration time, a clear block directly select the corresponding block as a fusion, for the border region, the wavelet decomposition on the basis of the pixel-based contrast method selected for processing. Platform: |
Size: 338944 |
Author:许国柱 |
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Description: 读入一幅256*256图像，将它分成8*8pixel的若干块，对每块做DCT变换，保留Z型顺序的若干变换系数，进行IDCT重构图像，计算重构图像的信噪比-Reading a 256* 256 image, it will be divided into several blocks of 8*8 pixel, keep each optimal Z transformation of sequence number, IDCT transform coefficient calculation reconstruction image reconstruction images,and the signal-to-noise ratio Platform: |
Size: 3072 |
Author:jiangxin |
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Description: 文是一种基于灰度共生矩阵的图像相似性检索算法，首先将图像分成互不重叠的子图像块，根据子图像
块中像素间灰度差别重新设置每个像素的灰度值为0或l，然后将整个图像重新划分成子块，对子块编码，最后借
助共生矩阵提取的不同方向的特征值来检索图像的相似性。实验结果表明本文算法对图像相似性的检索比传统
方法GLCM、CCM更有效，且检索效率较高，更重要的是此算法还可以反应不同方向上图像的相似度。-Man is an image based on gray level co-occurrence matrix of similarity search algorithm, the first image into non-overlapping sub-image block, the sub-image blocks of pixels gray Cibie reset each pixel grayscale value 0 or l, then the image re-divided into sub-blocks, pair block coding, and finally extracted with co-occurrence matrix eigenvalues in different directions to retrieve similar images. Experimental results show that the algorithm for image similarity retrieval method than the traditional GLCM, CCM is more effective and efficient retrieval, more importantly, the algorithm can also respond in different directions on the image similarity. Platform: |
Size: 416768 |
Author:周二牛 |
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Description: 一种跟踪方法，将图像分成若干的图像块，进行块匹配，很好的解决了遮挡问题，-A tracking method, the image is divided into a number of image blocks, the block matching, a good solution to the occlusion problem, Platform: |
Size: 2799616 |
Author:董晶晶 |
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Description: qtdecomp divides a square image into four equal-sized square blocks, and then tests each block to see if it meets some criterion of homogeneity. If a block meets the criterion, it is not divided any further. If it does not meet the criterion, it is subdivided again into four blocks, and the test criterion is applied to those blocks. This process is repeated iteratively until each block meets the criterion. The result can have blocks of several different sizes. Platform: |
Size: 747520 |
Author:fefe |
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Description: 为了提高图像加密算法的鲁棒性，提出了一种新的自适应图像加密算法。首先，把任意大小的灰度或彩
色图像分成2 × 2 子块 然后，用左上角子块的像素灰度值和Chebyshev 混沌映射构造与右上角子块等大的矩阵，用该
矩阵对右上角子块进行像素灰度值替换 最后，按顺时针对每个子块进行加密，直到左上角子块加密完毕。该算法不
依赖于图像的大小，而且适用于灰度图像和彩色图像，因而有很强的鲁棒性。同时灰度值扩散机制的引入使得该算
法具有良好的扩散性和扰乱性。-This paper presented a new self-adaptive image encryption algorithm so as to improve its robustness． Under
this algorithm， a gray image or color image was divided into 2 × 2 size blocks． A corresponding size of matrix in the top right
corner was created by the pixel gray-scale value of the top left corner under Chebyshev mapping． The gray-scale value of the
top right corner block was then replaced by the matrix created before． The remaining blocks were encrypted in the same
manner in clockwise until the top left corner block was finally encrypted． This algorithm is not restricted to the size of image
and it is suitable to gray images and color images， which leads to better robustness． Meanwhile， the introduction of gray-scale
value diffusion system equips this algorithm with powerful function of diffusion and disturbance． Platform: |
Size: 43008 |
Author:wangc |
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Description: Splicing operation may introduce inconsistencies in
organized as follows. In Section 2, we introduce scene
illumination estimation methods. In Section 3, the proposed
method based on illumination inconsistency is introduced.
Section 4 presents experimental results and discussion.
Section 5 concludes the paper.
many features. In the proposed method illuminant color
inconsistency is used to detect image splicing. A given color
image is divided into many overlapping blocks. Then a
classifier is used to adaptively select illuminant estimation
algorithm based on block content. Illuminant color is
estimated on each block, and the difference between the
estimation and reference illuminant color is measured. If the
difference is larger than a threshold, the corresponding block
is labeled as spliced block. Experiments show effectiveness of
the method.
Platform: |
Size: 274432 |
Author:Kiran |
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Description: DCT and Image Compression
In the JPEG image compression algorithm, the input image is divided into
8-by-8 or 16-by-16 blocks, and the two-dimensional DCT is computed for each
block. The DCT coefficients are then quantized, coded, and transmitted. The
JPEG receiver (or JPEG file reader) decodes the quantized DCT coefficients,
computes the inverse two-dimensional DCT of each block, and then puts the
blocks back together into a single image. For typical images, many of the
DCT coefficients have values close to zero these coefficients can be discarded
without seriously affecting the quality of the reconstructed image.
The example code below computes the two-dimensional DCT of 8-by-8 blocks
in the input image, discards (sets to zero) all but 10 of the 64 DCT coefficients
in each block, and then reconstructs the image using the two-dimensional
inverse DCT of each block. The transform matrix computation method is used.- DCT and Image Compression
In the JPEG image compression algorithm, the input image is divided into
8-by-8 or 16-by-16 blocks, and the two-dimensional DCT is computed for each
block. The DCT coefficients are then quantized, coded, and transmitted. The
JPEG receiver (or JPEG file reader) decodes the quantized DCT coefficients,
computes the inverse two-dimensional DCT of each block, and then puts the
blocks back together into a single image. For typical images, many of the
DCT coefficients have values close to zero these coefficients can be discarded
without seriously affecting the quality of the reconstructed image.
The example code below computes the two-dimensional DCT of 8-by-8 blocks
in the input image, discards (sets to zero) all but 10 of the 64 DCT coefficients
in each block, and then reconstructs the image using the two-dimensional
inverse DCT of each block. The transform matrix computation method is used. Platform: |
Size: 1024 |
Author:Eldhose |
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Description: 视频图像的人群密度检测，多种人群密度场景下人群计数算法：
算法功能:建立图像特征和图像人数的数学关系
算法输入:训练样本图像1,2…K
算法输出:模型估计参数 ，参考图像
算法流程：1)对训练样本图像进行分块处理(算法1.1)；
2)通过算法1.2，计算训练样本各个对应分块的ALBP特征归一化，再用K-means算法(可使用opencv等算法库实现，不再描述其算法)，将图像块分成k(k<K)类，获取k(k<K)个聚类中心，即为参考图像；
3)对分块的图像进行与参考图像进行匹配。使用算法1.2求取ALBP特征，并求取其相似度 ，将相似性集合作为新特征并形成一个归一化的新特征 。
4)按照行人面积占图像块面积的比例，以60 为分界，分布采用径向基核函数 和线性核函数 。K(xi,x)建立图像特征和图像人数的SVR(支持向量回归机)模型可使用opencv中的SVM或libsvm，输出模型估计参数 。
-Population density detection of video images, a variety of crowd density scenes crowd counting algorithm:
Algorithm functions: a mathematical relation between the image features and the number of images
Algorithm Input: training sample image 1,2 ... K
Algorithm output: model estimation parameters, reference image
Algorithmic process: 1) the training sample image into blocks (algorithm 1.1)
2) by 1.2 algorithm to calculate the corresponding training samples of each block ALBP features normalized, then K-means algorithm (algorithm can be used opencv library implementation, no longer describe the algorithm), the image block is divided into k (k <K) class, gets k (k <K) clustering centers, namely the reference image
3) conduct of image block matching with the reference image. 1.2 ALBP characterized using an algorithm to strike, and strike the similarity, the similarity of a set of new features and forming a normalized new features.
4) pedestrian area accounted for in Platform: |
Size: 4759552 |
Author:徐云华 |
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Search - image divided blocks