Description: 计算机视觉是在图像处理的基础上发展起来的新兴学科。计算机视觉从信息处理的层次研究视觉信息的认知过程，研究视觉信息处理的计算理论、表达与计算方法。本书系统地介绍了计算机视觉的重要理论与算法，包括图像特征提取，摄像机定标，立体视觉，运动视觉(或称序列图像分析)，由图像灰度恢复三维物体形状的方法，物体建模与识别方法以及距离图像分析方法等。-in computer vision image processing on the basis of the development of a new subject. Computer processing of visual information from the study on the levels of visual information cognitive process, the study of visual information processing theory. Expression and calculation methods. The book systematically introduces computer vision of the important theory and algorithms, including image feature extraction, camera calibration, stereo vision, sports vision (or image sequence analysis), gray-scale images from 3D object shape, Object Modeling and Recognition and the distance between image analysis methods. Platform: |
Size: 13978253 |
Author:谢志东 |
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Description: % demo_l2_l1 - This demo illustrates the TwIST % algorithm in the l2-l1 optimization problem % % xe = arg min 0.5*||A x-y||^2 + tau ||x||_1 % x % % where A is a generic matrix and ||.||_1 is the l1 norm. % After obtaining the solution we implement a debias phase % % For further details about the TwIST algorithm, see the paper: % % J. Bioucas-Dias and M. Figueiredo, "A New TwIST: Two-Step % Iterative Shrinkage/Thresholding Algorithms for Image % Restoration", IEEE Transactions on Image processing, 2007. % %% % Please check for the latest version of the code and papers at % www.lx.it.pt/~bioucas/TwIST % % Authors: Jose Bioucas-Dias and Mario Figueiredo, % Instituto Superior T閏nico, October, 2007 Platform: |
Size: 78228 |
Author:li123kai@126.com |
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Description: 计算机视觉是在图像处理的基础上发展起来的新兴学科。计算机视觉从信息处理的层次研究视觉信息的认知过程，研究视觉信息处理的计算理论、表达与计算方法。本书系统地介绍了计算机视觉的重要理论与算法，包括图像特征提取，摄像机定标，立体视觉，运动视觉(或称序列图像分析)，由图像灰度恢复三维物体形状的方法，物体建模与识别方法以及距离图像分析方法等。-in computer vision image processing on the basis of the development of a new subject. Computer processing of visual information from the study on the levels of visual information cognitive process, the study of visual information processing theory. Expression and calculation methods. The book systematically introduces computer vision of the important theory and algorithms, including image feature extraction, camera calibration, stereo vision, sports vision (or image sequence analysis), gray-scale images from 3D object shape, Object Modeling and Recognition and the distance between image analysis methods. Platform: |
Size: 13977600 |
Author:谢志东 |
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Description: 图像去噪是图像处理领域中的一个重要内容，图像去噪总是需要在抑制噪声和保持图像细节之间做折衷。小波变换作为一种新的信号处理工具，在信号去噪领域已得到了成功的应用。在传统的基于正交小波变换的图像去噪方法中，重建图像在边缘附近容易产生振荡从而造成边缘失真，噪声较严重时还会产生模糊边缘；利用冗余小波变换，可以克服正交小波变换去噪存在的不足, 进一步提高算法的去噪性能-Image denoising image processing is an important area of content, image denoising is always the need to suppress noise and maintain a compromise between image detail. Wavelet transform as a new signal processing tools, in the field of signal de-noising has been applied successfully. In the traditional orthogonal wavelet transform based image denoising methods, the reconstructed image at the edge near the oscillation and thus prone to cause the edge of distortion, noise will also produce more serious when the fuzzy edge the use of redundant wavelet transform, orthogonal wavelet can be overcome Transform Denoising deficiencies, further improving the performance of denoising algorithms Platform: |
Size: 1788928 |
Author:李胖子 |
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Description: 该程序是完成各种经典办色调图像处理算法，及基于图像特征的半色调方法和机遇图像极小乡四渡的半色调方法。-Completion of the program are to do a variety of classic color image processing algorithms, and image-based features of methods and opportunities halftone image of a very small rural four Kuantu halftoning methods. Platform: |
Size: 253952 |
Author:renxiaoling |
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Description: 一种实现超分辨率图像处理的新算法,本算法在综合前人算法的基础上，做了很大改进。很适合图像处理。-An implementation of the new super-resolution image processing algorithms, the algorithm in integrated algorithm based on the predecessors has done a lot of improvements. Very suitable for image processing. Platform: |
Size: 2048 |
Author:lcy |
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Description: 该程序可以实现二值图像的细化，采用的不是matlab自带的函数算法进行处理，而是采用了一种新算法进行细化，比原算法有很大改进，值得研究！-The program can achieve binary image thinning using matlab built-in function is not processing algorithms, instead of using a new algorithm refinement, a significant improvement over the original algorithm, is worth studying! Platform: |
Size: 1024 |
Author:成林 |
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Description: Block Matching Algorithms for Motion Estimation
This project contains the project report and source code by Aroh Barjatya for Digital Image Processing Class at Utah State University.
Following is a short description of the m files in this zip
motionsEstAnalysis.m Script to execute all Algorithms
motionEstES.m Exhaustive Search Algorithm
motionEstTSS.m Three Step Search Algorithm
motionEstNTSS.m New Three Step Search Algorithm
motionEstSESTSS.m Simple And Efficient Search Algorithm
motionEst4SS.m Four Step Search Algorithm
motionEstDS.m Diamond Search Algorithm
motionEstARPSm Adaptive Root Pattern Search Algorithm
costFuncMAD.m Mean Absolute Difference Function
minCost.m minimum cost among macro blocks
motionComp.m motion compensated image creator
imgPSNR.m finds image PSNR w.r.t. reference image
The test images can be found at http://cc.usu.edu/~arohb/caltrain.zip-Block Matching Algorithms for Motion Estimation
This project contains the project report and source code by Aroh Barjatya for Digital Image Processing Class at Utah State University.
Following is a short description of the m files in this zip
motionsEstAnalysis.m Script to execute all Algorithms
motionEstES.m Exhaustive Search Algorithm
motionEstTSS.m Three Step Search Algorithm
motionEstNTSS.m New Three Step Search Algorithm
motionEstSESTSS.m Simple And Efficient Search Algorithm
motionEst4SS.m Four Step Search Algorithm
motionEstDS.m Diamond Search Algorithm
motionEstARPSm Adaptive Root Pattern Search Algorithm
costFuncMAD.m Mean Absolute Difference Function
minCost.m minimum cost among macro blocks
motionComp.m motion compensated image creator
imgPSNR.m finds image PSNR w.r.t. reference image
The test images can be found at http://cc.usu.edu/~arohb/caltrain.zip Platform: |
Size: 118784 |
Author:Yashil |
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Description: Euclidean Distance Transform has been widely studied in computational geometry, image processing, computer graphics and pattern recognition. Euclidean distance has been computed through different algorithms like parallel, linear time algorithms etc. On the basis of efficiency, accuracy and numerical computations, existing and proposed techniques has been compared. This study proposed a new technique of finding Euclidian distance using sequential algorithm. An experimental evaluation has shown that proposed technique has reduced the drawbacks of existing techniques. And the use of sequential algorithm scans has reduced the computational cost. Platform: |
Size: 101376 |
Author:yasora |
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Description: With the fast development of the computer technology and information processing technology, the problem of information security is becoming more and more important. Information hiding is usually used to protect the important information from disclosing when it is transmitting over an insecure channel. Digital image encryption is one of the most important methods of image information hiding and camouflage. The image encryption techniques mainly include compression methodology, modern cryptography mechanism, chaos techniques, DNA techniques, and so on. In this paper, we summarize the main encryption algorithms and classify them based on the means. In particular, chaos-based and DNA cryptography-based image encryption algorithms are illustrated and analyzed in detail. Finally, the future direction in this field is discussed. Platform: |
Size: 76800 |
Author:mrinal |
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Description: 视频跟踪算法,关于在视频中跟踪移动目标的图像处理程序-The Reading People Tracker is a software for tracking people in camera images for visual surveillance purposes. It originates from research work on people tracking for automatic visual surveillance systems for crime detection and prevention. It was built within the context of two PhD theses (by AM Baumberg and NT Siebel) and contains state-of-the art image processing algorithms. It is easily maintainable and well documented. Therefore it can (and has already been) easily be adapted to new requirements and different projects. The Reading People Tracker contains the necessary functionality to read video sequences from hard disk or a video camera (IEEE1394/DV), to manipulate the images with image filters and to analyse them with a number of detection and tracking modules. Platform: |
Size: 429056 |
Author:wan |
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Description: First in a series
This lesson is the first lesson in a new series intended to teach you how to use Java to create special effects with images by directly
manipulating the pixels in the images.
Not a lesson on JAI
If you arrived at this lesson while searching for instructions on how to use the Java Advanced Imaging (JAI) API, you are certainly welcome to
be here. However, that is not the purpose of the lessons in this series. (Maybe I will write a series on that topic later.) The purpose of this
series is to get right down in the mud and to learn how to implement many of the algorithms that are commonly used to create special effects
with images by working directly with the pixels.
Manipulate pixels directly and individually
In this lesson, I will provide and explain a program that makes it easy to:
•
•
Manipulate and modify the pixels that belong to an image
Display the modified image along with the original image for easy comparison in abefore and after sense Platform: |
Size: 599040 |
Author:yogesh |
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Description: For a particularly long time, automatic diagnosis of diabetic retinopathy digital
fundus images has been an active research topic in the medical image processing
community. The research interest is justified by the excellent potential for new
products in the medical industry and significant reductions in health care costs.
However, the maturity of proposed algorithms cannot be judged due to the lack
of commonly accepted and representative image with a verified ground
truth and strict uation protocol. In this study, an uation methodology is proposed
and an image with ground truth is described-For a particularly long time, automatic diagnosis of diabetic retinopathy digital
fundus images has been an active research topic in the medical image processing
community. The research interest is justified by the excellent potential for new
products in the medical industry and significant reductions in health care costs.
However, the maturity of proposed algorithms cannot be judged due to the lack
of commonly accepted and representative image with a verified ground
truth and strict uation protocol. In this study, an uation methodology is proposed
and an image with ground truth is described Platform: |
Size: 2048 |
Author:mohammad |
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Description: This code is as per SPECT reconstruction By: Martin Š ámal Charles @ Regional
Training Workshop on Advanced Image Processing of SPECT Studies 19-23 April 2004.
The principle of the iterative algorithms is to reconstruct an image of a tomographic slice projections by successive
estimates. The projections corresponding to the current estimate are compared with
the measured projections. The result of the comparison is used to modify the current
estimate, thereby creating a new estimate.
The algorithms differ in the way the measured and estimated projections are compared and the kind of correction applied to the current estimate. The process is initiated by arbitrarily creating a first estimate - for example, a uniform image (all pixels equal zero, one, or a mean pixel value,…). Corrections are carried out either as addition of differences or multiplication by quotients between measured and
estimated projections.-This code is as per SPECT reconstruction By: Martin Š ámal Charles @ Regional
Training Workshop on Advanced Image Processing of SPECT Studies 19-23 April 2004.
The principle of the iterative algorithms is to reconstruct an image of a tomographic slice projections by successive
estimates. The projections corresponding to the current estimate are compared with
the measured projections. The result of the comparison is used to modify the current
estimate, thereby creating a new estimate.
The algorithms differ in the way the measured and estimated projections are compared and the kind of correction applied to the current estimate. The process is initiated by arbitrarily creating a first estimate - for example, a uniform image (all pixels equal zero, one, or a mean pixel value,…). Corrections are carried out either as addition of differences or multiplication by quotients between measured and
estimated projections. Platform: |
Size: 2048 |
Author:keyvan |
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Description: Edge detection algorithms are important tools in image
processing applications for carrying out much information and
being relatively easy to produce. Sobel Canny and logarithmic
algorithms [1] are among several edge detection algorithms
used frequently nowadays. The ution of such edge detection
algorithms is an old problem. Authors [1][3] tend to use visual
uation that limits the comparison between different edge
images. In this paper, we present a new edge enhancement
method and five different measures that can be used to
statistically uate edge detection algorithms. The new edge
enhancement method is based on cooperation between different
edge detection algorithms. The new edge preserves the
advantages of each edge image. Experimental results using two
edge detection algorithms proved the efficiency of this method.-Edge detection algorithms are important tools in image
processing applications for carrying out much information and
being relatively easy to produce. Sobel Canny and logarithmic
algorithms [1] are among several edge detection algorithms
used frequently nowadays. The ution of such edge detection
algorithms is an old problem. Authors [1][3] tend to use visual
uation that limits the comparison between different edge
images. In this paper, we present a new edge enhancement
method and five different measures that can be used to
statistically uate edge detection algorithms. The new edge
enhancement method is based on cooperation between different
edge detection algorithms. The new edge preserves the
advantages of each edge image. Experimental results using two
edge detection algorithms proved the efficiency of this method. Platform: |
Size: 873472 |
Author:sacoura |
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Description: Edge detection is widely used in image processing, image recognition and computer vision. Tradition edge detection
methods have a lot of disadvantages. This paper presents a new edge detection algorithm base on Matching Pursuit
(MP). Our method has four steps. Firstly, the color image is converted to gray Image. Secondly, the residual part of
Matching Pursuit algorithm with the Wavelet Packet dictionary is extracted. Thirdly, the Gaussian Filter is applied to
remove the additional parts of the previous image and finally, the Ostu’s thresholding method converts image to
binary form. We compared our algorithm with the tradition methods like Prewitt, Sobel, Laplacian of Gaussian (LOG)
and Canny operators. Results show that our algorithm has high value of Performance parameters such as PR, PSNR
and FOM compared to other algorithms. Platform: |
Size: 1069056 |
Author:sacoura |
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Description: sar图像去噪的几种新的方法，在matlab环境中自动识别连通区域的大小,一些自适应信号处理的算法。- Several new methods sar image denoising, Automatic identification in the matlab environment the size of the connected area, Some adaptive signal processing algorithms. Platform: |
Size: 7168 |
Author:朱冬跃 |
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Description: Similar to other digital assets, deep neural network
(DNN) models could suffer from piracy threat initiated by insider
and/or outsider adversaries due to their inherent commercial
value. DNN watermarking is a promising technique to mitigate
this threat to intellectual property. This work focuses on black-
box DNN watermarking, with which an owner can only verify
his ownership by issuing special trigger queries to a remote
suspicious model. However, informed attackers, who are aware
of the watermark and somehow obtain the triggers, could
forge fake triggers to claim their ownerships since the poor
robustness of triggers and the lack of correlation between the
model and the owner identity. This consideration calls for new
watermarking methods that can achieve better trade-off for
addressing the discrepancy. In this paper, we exploit frequency
domain image watermarking to generate triggers and build our
DNN watermarking algorithm accordingly. Since watermarking
in the frequency domain is high concealment and robust to
signal processing operation, the proposed algorithm is superior to
existing schemes in resisting fraudulent claim attack. Besides, ex-
tensive experimental results on 3 datasets and 8 neural networks
demonstrate that the proposed DNN watermarking algorithm
achieves similar performance on functionality metrics and better
performance on security metrics when compared with existing
algorithms. Platform: |
Size: 374457 |
Author:bamzi334 |
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Search - new algorithms in image processing