Description: 数字图像处理实验
根据原图像的直方图，发现背景和目标的分割值大约在130左右，并将灰度图像转为二值图像，分割效果比较理想。
图像处理实验（六）图像压缩与编码
实验目的： 学习JPEG压缩编码
实验内容：
一．实现基本JPEG的压缩和编码分三个步骤：
1． 首先通过DCT变换去除数据冗余；
2． 使用量化表对DCT系数进行量化；
3． 对量化后的系数进行Huffman编码。-digital image processing experiments based on the original image histogram, found background and objectives of the divided about the value of around 130 and two gray-scale image to image, Segmentation more satisfactory results. Image processing experiments (6) Image Compression and Coding of the experiment : Learning JPEG compression coding experiment : one. Basically JPEG compression and coding in three steps : 1. First through DCT remove data redundancy; 2. Using quantitative table right DCT coefficient quantization; 3. Right quantized coefficients of Huffman coding. Platform: |
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Author:qq |
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Description: k-均值聚类算法实现灰度图像分割，输入图像矩阵和聚类中心个数，返回为最终的聚类中心和图像中每个像素所属类的编号（对应于图像矩阵）-k-means clustering algorithm to achieve gray-scale image segmentation, the input image matrix and the number of cluster centers, the return for the final image of the cluster centers and their respective categories in each pixel number (corresponding to the image matrix) Platform: |
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Author:cc |
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Description: otsu自适应阈值分割OTSU算法也称最大类间方差法，是图像分割里基于点的全局阈值选取方法中的一种，诞生于1978年，作者是Otsu。这种方法以其计算简单、稳定有效，一直广为使用，至今仍在matlab的图像处理工具箱里作为灰度图像单阈值自动选取的标准算法-Otsu adaptive threshold segmentation algorithm OTSU also known Otsu method is based on the point of image segmentation in the global threshold selection methods, was born in 1978, the author is Otsu. This method of its calculation is simple, stable and efficient, has been widely used in still image processing toolbox matlab as a gray image is automatically selected a single threshold value of the standard algorithm Platform: |
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Author:子羽 |
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Description: 在指纹特征提取中，结合方向图和图像局部灰度方差对指纹图像进行分割，然后再进行阈值分割去处边缘效应得出较好的分割结果。-In the fingerprint feature extraction, the combination of pattern and image local variance of gray-scale fingerprint image segmentation, and then conducted threshold segmentation edge effects come to a better place for the segmentation results. Platform: |
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Author:zizou |
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Description: 经典区域生长源码(区域增长),比起灰度阈值法有不可比拟的优势,一旦尝试,欲罢不能啊,只是,在实时性应用方面还有待改进,m代码编写易懂,易用,易改写成其他语言,如果改写成c,应该速度有所提高.请尽情享用-Classical region growing source (regional growth), compared to gray-scale threshold method has unparalleled advantages, once the attempt to stop ah, but, in real-time applications have yet to be improved, m coding easy to understand, easy to use, easy to rewritten into other languages, if rewritten into c, the speed should be improved. please enjoy Platform: |
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Author:zz |
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Description: OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images.- OTSU Gray-level image segmentation using Otsu s method.
Iseg = OTSU(I,n) computes a segmented image (Iseg) containing n classes
by means of Otsu s n-thresholding method (Otsu N, A Threshold Selection
Method from Gray-Level Histograms, IEEE Trans. Syst. Man Cybern.
9:62-66 1979). Thresholds are computed to maximize a separability
criterion of the resultant classes in gray levels.
OTSU(I) is equivalent to OTSU(I,2). By default, n=2 and the
corresponding Iseg is therefore a binary image. The pixel values for
Iseg are [0 1] if n=2, [0 0.5 1] if n=3, [0 0.333 0.666 1] if n=4, ...
[Iseg,sep] = OTSU(I,n) returns the value (sep) of the separability
criterion within the range [0 1]. Zero is obtained only with images
having less than n gray level, whereas one (optimal value) is obtained
only with n-valued images. Platform: |
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Author:ltrko9kd |
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Description: 摘 要
文章以空间监控系统为背景,深入研究了JPEG图像压缩标准的实现方法,并基于FPGA对其进行了实现和优化。文中给出了详细的实现方法和优化过程,测试表明达到了很好的效果。
简单介绍了有损静态图像压缩当前有两种比较流行的标准JPEG和JPEG2000。说明了用JPEG方法压缩的原因。
介绍JPEG基本原理：JPEG对灰度图像的压缩处理过程主要包括:图像分割,离散余弦变换(DCT),量化(Quantization),“Z”形排序(Zigzag Scan),差分脉冲编码调制(Differential Pulse Code Modulation,DPCM)对直流系数(DC),行程长度编码(Run-Length Encoding,RLE)对交流系数(AC),霍夫曼(Huffman)编码等。
JPEG标准的特点是离散余弦变换。
比较详细介绍压缩系统的构成和实现。实现提及步骤， JPEG压缩模块设计和编码模块实现细节。
-Abstract
Article in the space monitoring system for the background, in-depth study of the JPEG image compression standard implementation methods and carried out based on FPGA implementation and optimization. In this paper, a detailed method of implementation and optimization of the process, testing showed that to achieve good results.
Easy introduction of harmful static image compression has two kinds of comparisons that the current popular standard JPEG and JPEG2000. Illustrated by the reasons for JPEG compression method.
JPEG introduce the basic principles: JPEG compression of gray-scale image processing include: image segmentation, discrete cosine transform (DCT), quantization (Quantization), "Z"-shaped sort (Zigzag Scan), differential pulse code modulation (Differential Pulse Code Modulation, DPCM) on the DC coefficient (DC), Run Length Encoding (Run-Length Encoding, RLE) of the exchange coefficient (AC), Hoffman (Huffman) coding.
JPEG standard is characterized by discrete Platform: |
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Author:压子 |
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Description: 摘 要:针对茄子图像的灰度和颜色特点,利用MATLAB中丰富的图像处理函数,分别进行了色差分割和色调分割。在
色调分割中,采用了自动选取阈值的Otsu法。在去除残留噪音的处理中,采用标注的方法对二值图像的各连通区域进行面积
统计。保留最大面积的区域,从而使分割效果大大改善。利用多参数来衡量分割效果,使评价做到最大程度的客观、合理。-Based on the gray- level and color characteristics of eggp lant image, hue and color- difference segmentation were
conducted by using the rich image p rocessing functions embedded inMATLAB. The auto threshold- adap tivemethod ofOtsu operation
was specially used for hue segmentation. And upon the elimination of the residue noise, labelingmethod for statistical calculation was
introduced for the connected regions of the binary image. Themaximum areaswere p reserved to imp rove segmentation effects. In addi2
tion, multi- indiceswere app lied to assess the effect of segmentation, in order to get impersonal and reasonable assessment Platform: |
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Author:renyh |
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Description: 基于阈值分割的运动车辆检测跟踪，在视频中按灰度阈值不同进行图像分割，并标记结果。-Threshold-based segmentation to track the movement of vehicles detected in the video by a different gray level threshold for image segmentation, and mark the results. Platform: |
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Author:哈田甜哈 |
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Description: 将K均值算法用于图像分割,输入的是彩色图像,转换为灰度图像进行分割,输出结果为灰度图像.利用灰度做为特征对每个像素进行聚类,由于光照等原因,有时应该属于一个物体的像素,其灰度值也会有很大的差别,可能导致对该像素的聚类发生错误.在分割结果中,该物体表面会出现一些不同于其它像素的噪声点,因此,算法的最后,对结果进行一次中值滤波,以消除噪声,达到平滑图像的作用-The K means algorithm for image segmentation, the input is a color image, convert to grayscale image segmentation, the output of grayscale images. The use of gray as the characteristics of each pixel clustering, due to light and other reasons, and sometimes should belong to an object pixel, its gray value will also be very different, may lead to clustering of the pixel error has occurred. in the segmentation results, the surface, there would be different from other pixel noise points, so , the algorithm Finally, the results of a median filter to eliminate noise, to the role of smoothing the image Platform: |
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Author:caoliang |
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Description: 分水岭分割方法，是一种基于拓扑理论的数学形态学的分割方法，其基本思想是把图像看作是测地学上的拓扑地貌，图像中每一点像素的灰度值表示该点的海拔高度，每一个局部极小值及其影响区域称为集水盆，而集水盆的边界则形成分水岭。分水岭的概念和形成可以通过模拟浸入过程来说明。在每一个局部极小值表面，刺穿一个小孔，然后把整个模型慢慢浸入水中，随着浸入的加深，每一个局部极小值的影响域慢慢向外扩展，在两个集水盆汇合处构筑大坝，即形成分水岭。
-Watershed segmentation method is a topology-based theory of mathematical morphology segmentation method, the basic idea is the image as a geodesic topology on the landscape, the image pixel gray value of each point indicates that the point of the altitude, Each local minimum value and its impact area known as the catchment basins, while the catchment basins of the border, however, the formation of a watershed. Watershed concepts and immersed in the process of the formation can be illustrated through simulation. A local minimum in each surface, piercing a small hole, and then slowly immersed in water the whole model, with the deepening of immersion, each local minimum value of the influence domain slowly expanded outward, in the two catchment the confluence of building the dam basin, namely, the formation of a watershed. Platform: |
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Author:王帅 |
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Description: In this project ,we propose a color based segmentation method that uses the c means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color based segmentation algorithm with k means means to convert a given gray level MR image in to a color space image and then separate the position of tumor objects from other items of an MR image by using c means clustering
And histogram clustering .Experiments demonstrates that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.
-In this project ,we propose a color based segmentation method that uses the c means clustering technique to track tumor objects in magnetic resonance (MR) brain images. The key concept in this color based segmentation algorithm with k means means to convert a given gray level MR image in to a color space image and then separate the position of tumor objects from other items of an MR image by using c means clustering
And histogram clustering .Experiments demonstrates that the method can successfully achieve segmentation for MR brain images to help pathologists distinguish exactly lesion size and region.
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Author:pramod |
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Description: 出了一种新的图像分割方法。这种分割方法首先利用粗糙集理论将图像按照一定的规则划分为
大小相等的若干图像子块，而后利用蒙特卡罗方法基本原理对划分的图像子块进行一定规模的随机抽样，以随机抽
样所得的图像子块为样本进行粗糙熵计算，用所得最大粗糙熵所对应的灰度值为分割阀值对图像进行分割，在采用
较小的图像子块划分以取得更好的分割效果的情况下，极大的提高了算法的分割速度。通过对测试图像的
MATLAB仿真试验验证了算法在降低计算机消耗方面的有效性，且所得的分割阀值也令人满意。-The image segmentation algorithm was presented．First of all，it divides the image into some equal SI‘Ze image sub
—pieces according with some rules，carries out certain scale random sampling on the image sub—pieces using Monte Carlo
Methods，and computes the rough entropy of the sample，and then divides the image by the image gray scale corresponding to the maximum rough entropy．The speed of the image segmentation is largely improved，while adopting the less image sub—
pieces to get better segmentation effect．And it has been confirmed in reducing the consumption of the computer is very effective in experiments using MATLAB，and the threshold is satisfied． Platform: |
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Author:王文 |
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Description: 本文重点研究了面积法对车流量进行统计。在研究算法过程中主要用到了车辆图像检测相关的灰度化、滤波、图像增强、锐化等图像处理基础知识，并将这些知识的算法进行了比较研究。进而用到了阈值分割、边缘检测、以及形态学操作等图像分割技术以及车辆的检测和提取算法。最后设计了一种实时可靠的统计算法。-This paper focuses on the area method for traffic statistics. In the study of algorithms used in the vehicle during the main test-related gray scale image, filtering, image enhancement, sharpening and other image processing basics and knowledge of the algorithms were compared. Then use a threshold segmentation, edge detection, and morphological operations such as image segmentation, and vehicle detection and extraction algorithms. The final design of a real-time reliable statistical algorithms. Platform: |
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Author:何呈 |
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Description: matlab的图像分割程序：根据图像中物体的灰度分布情况，选取一个近似阈值作为初始阈值，一个较好的方法就是将图像的灰度均值作为初始阈值；然后通过分割图像和修改阈值的迭代过程获得认可的最佳阈值。-Matlab image segmentation: distribution of images of objects in gray, select an approximate threshold value as the initial threshold of a better way is the average gray value of image as the initial threshold image segmentation and modify the threshold of the iterative process to obtain the optimal threshold for recognition. Platform: |
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Author:张雷 |
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Description: 针对MATLAB图像处理，从最基础的灰度化到滤波，到分割等，详细介绍了MATLAB对图像的处理。(On MATLAB image processing, from the most basic gray to filter, to, such as segmentation of MATLAB image processing was introduced in detail.) Platform: |
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Author:lalalano
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Search - gray image segmentation in matlab