Description: 基于模糊对比度的图像增强方法，大致过程仍然是先把图像从空间域映射到模糊域，在模糊域内通过定义一个局部对比度算子，然后通过对凸函数的加强来放大像素邻域的各像素之间的差异。
-Based on the fuzzy contrast image enhancement method, the general process is still the first images from space domain is mapped to the fuzzy field in fuzzy field through the define a local contrast operator, and then the convex function to enlarge the strengthening of pixels each neighborhood pixel differences.
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Author:艾可 |
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Description: 主要是利用对比增强来处理图像 利用了模糊集以及模糊熵理论-The main use of contrast enhancement to the image processing using fuzzy sets and fuzzy entropy theory Platform: |
Size: 1024 |
Author:艾可 |
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Description: 数字图像在采集过程中,由于照明或物体本身等原因,经常会出现目标区域对比度低、细节模糊的情况,需要经过进一步的预处理才能使用。一种较为有效的对比度拉升技术,它通过选择合理的分段点来实现图像增强。-The digital image acquisition process, due to reasons such as lighting or object itself, often the target area with low contrast, fuzzy details, you need to go through further pre-treatment can be used. A more effective contrast pulled it by selecting the staging point for image enhancement. Platform: |
Size: 2940928 |
Author:郭涵 |
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Description: 本文主要介绍遗传算法的基本理论，叙述遗传算法在图像增强的的主要应用，即将原始图像变得更加清晰，特征变得更加明显。
现今关于图像增强的算法有很多，而这些算法大多是基于退化函数或者点扩展函数的知识进行图像处理的。当图像出现模糊或噪声影响大时，设计出的图像清晰化的效果肯定不够理想，因此有必要对图像进行增强处理。于是，可利用到遗传算法这种成熟稳定的仿生物进化的全局寻优算法，进行图像增强，由于遗传算法控制参数少、自适应度高，将选择该方法对图像退化分别进行不同的清晰化处理. 这样既增强了图像的对比度,又克服了传统直方图均衡化处理所造成的灰度级损失等缺点。
通过实验去表明，遗传算法从全局寻优的角度出发，能够较为精确地估计退化系统函数。和传统的线性增强、直方图均衡进行比较。实验结果表明该方法能改善原图像视觉效果，便于之后的图像分析。
-This paper mainly introduces the basic theory of genetic algorithm, genetic algorithm (ga) in the main application of image enhancement, the original image is more clear, characteristic becomes more obvious.
Today about the image enhancement algorithm are many, and most of these algorithms is based on the degradation function or the knowledge of the point spread function of image processing. When the image appears fuzzy or noise influence, designed the image clarity of effect must not ideal, therefore it is necessary to enhance the image. Then, genetic algorithm is available to the mature and stable evolution of the global optimization algorithm, for image enhancement, due to less genetic algorithm control parameters, since the high fitness, will choose the method of image degradation, respectively, to manipulate the different motivation. It can enhance the image contrast, and overcome the traditional histogram equalization processing grayscale loss caused by the faults.
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Size: 1670144 |
Author:古志榮 |
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Description: 课程的目的学习了解BMP的图像的结构，学会对BMP图像进行各种处理，图像平滑是指用于突出图像的宽大区域、低频成分、主干部分或抑制图像噪声和干扰高频成分，使图像亮度平缓渐变，减小突变梯度，改善图像质量的图像处理方法。数字图像处理中图像锐化同样是一个重要的部分，其目的有两个：一是使灰度反差增强，增强图像的边缘，使模糊的图像变得清晰起来；这种模糊不是由于错误操作，就是特殊图像获取方法的固有影响。二是提取目标物体的边界，对图像进行分割，便于目标区域的识别等。通过图像的锐化，使得图像的质量有所改变，产生更适合人观察和识别的图像。-Course learning to understand the purpose of the structure of BMP image, learn to various processing of BMP image, the image smooth refers to the large area is used to highlight the image, the low frequency component, trunk or suppress image noise and interference of high frequency components, make the image brightness flat gradient, gradient decrease mutations, improve image quality of the image processing methods. Digital image processing, image sharpening, is also an important part of its purpose has two: one is to make the gray contrast enhancement, enhance image edges, makes fuzzy image become clear This fuzzy is not due to wrong operation, it is the inherent influence of special image acquisition method. 2 it is to extract the boundary of the target object, the image segmentation, to facilitate the identification of the target area and so on. Through image sharpening, makes the quality of the image change, to create more suitable for human observation and identification of the i Platform: |
Size: 2446336 |
Author:chen |
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Description: 用模糊增强的方法增加原图像的对比度，以便用于后续分类和分割-Fuzzy enhancement method of increasing the contrast of the original image, so that for subsequent classification and segmentation Platform: |
Size: 1024 |
Author:小坏包 |
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Description: 基于自动选择阈值的模糊增强方法，对图像对比度增强有不错的效果-The fuzzy enhancement method based on automatic selection threshold has good effect on image contrast enhancement. Platform: |
Size: 8192 |
Author:唐迎春 |
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Description: 针对基于小波变换的红外图像增强方法视觉效果不够理想的缺点, 提出了一种基于平稳小波变换和Retinex 的红外图像增强方法, 利用Retinex 增强算法增强图像的视觉效果, 并改善其亮度均匀性。首先, 对红外图像经平稳小波变换后的最大尺度低频子带图像进行多尺度Retine x 增强 然后, 利用贝叶斯萎缩阈值法对高频子带图像进行阈值去噪, 并根据低频子带图像的局部对比度和模糊规则计算高频子带的增益系数, 从而得到增强后的高频子带图像 最后, 由低频子带图像和高频子带图像重构得到增强后的图像。针对大量图像进行了实验和增强效果的定性与定量评价, 并与双向直方图均衡法、二代小波变换法、Curvelet 变换法和多尺度Retinex法作了比较。结果表明, 所提出的方法增强了图像细节, 抑制了噪声, 并明显改善了图像的整体视觉效果。-As infrared image enhancement method based on wavelet transformation has the problem of unperfect visual effect , and Retinex enhancement algorithm can enhance visual effect of the image by improving brightness uniformity , amethod based on stationary wavelet transformation and Retinexis proposed.Firstly , the infrared image is decomposed into high-frequency detail and low-frequency approximation components at various resolutions, and the low frequency subband image of the largest scale is enhanced by multiscale Retinex algorithm.Then, the highfrequency subband images are denoised by Bayesian shrinkage method, and the gain coefficients of high-frequency subbands are available by calculating the local contrast of the enhanced low-frequency subband based on fuzzy rules to get the enhanced high-frequency subband images .Finally, the enhanced image is reconstructed by the low-frequency subband and high-frequency subbands .Experiments with qualitative and quantitative uation are carried ou Platform: |
Size: 479232 |
Author:kiel |
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Search - fuzzy contrast enhancement