Description: 这是一个在图象像素亮度中隐藏信息的算法，他能实现在图象像素的亮度值嵌入信息-This is a pixel in the image brightness information was concealed in the algorithm, he is able to achieve in the brightness of image pixels embedded value information Platform: |
Size: 3072 |
Author:杨永 |
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Description: 嵌入水印后的图像与原
始图像在视觉效果上几乎一样,只在亮度上稍有不
图6 仿真实验结果
图7 仿真实验结果
同,提取出的水印图像与原图像基本一致。-embedded watermark image with the original image in the visual effects are almost identical, only slight brightness on the map six simulation results Figure 7 with the simulation results. extract the watermark image with basically the same as the original image. Platform: |
Size: 1024 |
Author:江力 |
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Description: 本软件可以生成MandlBrot集、Julia集的图形，以及随机迭代法、Newton迭代法生成分形图象。另外，本系统还提供了简单的图象处理功能，比如图象的灰度化、二值化、图象的轮廓提取、彩色浮雕、亮度增加、Gamma校正、反色等。
-The software can generate MandlBrot sets, Julia Sets graphics, and random iteration, Newton iteration Health fractal images. In addition, the system also provides a simple image processing functions, such as gray-scale images, two values, the contours of the image extraction, Color relief, increased brightness, gamma correction, and other anti-Israel. Platform: |
Size: 413696 |
Author:acai17 |
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Description: 在一个图像中检测目标是图像分割的一个例子。为分割连通目标，时常用Watershed变换。如果把一幅图像看做一个具有山(高亮度)和低谷(低亮度)的表面，那么这个变换在一幅图像中找亮度低谷。-in an image detection of image segmentation is a case in point. Segmentation of connectivity, often used Watershed transform. If an image is seen as a Hill (high-brightness) and the bottom (low brightness) of the surface, Well, this transformation in an image brightness for a low ebb. Platform: |
Size: 2048 |
Author:何子鸣 |
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Description: 亮度人脸检测算法，能快速识别人脸，精度高，速度快-Brightness of face detection algorithm to quickly identify human faces, high precision, fast Platform: |
Size: 1024 |
Author:范一峰 |
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Description: Land关于人类视觉的亮度和色彩恒常性的最近一个retinex算法模型已经实现并通过了图像处理实验的测试。 早先的研究虽然确定了Land的retinex算法的数学基础,但是他的亮度理论却并没有得到广泛的图像处理实验的支持。我们应该因为这种Retinex算法作为人类光亮和色彩知觉的模型的准确性定义一个没有特例的实际的retinex的实现方式。-Land on the human visual brightness and color constancy of a recent Retinex algorithm model has been achieved through the image processing experimental testing. Although previous studies have identified a Land Platform: |
Size: 2931712 |
Author:曾和 |
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Description: 彩色图像分形压缩，由R,G，B中确定一个R块与D块的匹配位置，其他二原色只需在同一个D块位置匹配即可，只改变对应的亮度和偏移量即可，比SFC的方法节省时间。-Fractal color image compression, by the R, G, B defined in a R Block and D Block matching location, the other two primary colors just in the same location matching block D can only change the corresponding brightness and can offset than SFC method to save time. Platform: |
Size: 611328 |
Author:鞠金玲 |
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Description: 在图像处理中如何进行视频处理，如何从yuv格式的序列中提取出亮度信息，这是后面对视频处理的基础。-In image processing for video How to deal with how to format yuv sequence information extracted brightness, this is the basis of the face of video processing. Platform: |
Size: 64512 |
Author:wangxuyu |
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Description: Phase Based Template Matching: Phase information is used for matching the input imagery with the template. Both the images are filtered with canny edge detector. The timing efficiency is introduced by implementing skipping steps while doing correlation. The advantage of Phase based correlation technique is that it shows good response against shift/brightness variation and noise addition i.e. salt & pepper/Gaussian noise [1,2]. Templates includes small portion of cropped from input imagery with gaussian noise introduced in them. Platform: |
Size: 71680 |
Author:zhangxq |
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Description: Convert a color image between color representations.
B = COLORSPACE(S,A) converts the color representation of image A
where S is a string specifying the conversion. S tells the
source and destination color spaces, S = dest<-src , or
alternatively, S = src->dest . Supported color spaces are
RGB R G B Red Green Blue (ITU-R BT.709 gamma-corrected)
YPbPr Luma (ITU-R BT.601) + Chroma
YCbCr / YCC Luma + Chroma ("digitized" version of Y PbPr)
YUV NTSC PAL Y UV Luma + Chroma
YIQ NTSC Y IQ Luma + Chroma
YDbDr SECAM Y DbDr Luma + Chroma
JPEGYCbCr JPEG-Y CbCr Luma + Chroma
HSV / HSB Hue Saturation Value/Brightness
HSL / HLS / HSI Hue Saturation Luminance/Intensity
XYZ CIE XYZ
Lab CIE L*a*b* (CIELAB)
Luv CIE L*u*v* (CIELUV)
Lch CIE L*ch (CIELCH)-Convert a color image between color representations. B = COLORSPACE (S, A) converts the color representation of image A where S is a string specifying the conversion. S tells the source and destination color spaces, S = ' dest <-src' , or alternatively, S = ' src-> dest' . Supported color spaces are ' RGB' R' G' B ' Red Green Blue (ITU-R BT.709 gamma-corrected)' YPbPr ' Luma (ITU-R BT.601 )+ Chroma ' YCbCr' /' YCC' Luma+ Chroma ( " digitized" version of Y' PbPr) ' YUV' NTSC PAL Y' UV Luma+ Chroma ' YIQ' NTSC Y' IQ Luma+ Chroma ' YDbDr' SECAM Y ' DbDr Luma+ Chroma ' JPEGYCbCr' JPEG-Y' CbCr Luma+ Chroma ' HSV' /' HSB' Hue Saturation Value/Brightness' HSL ' /' HLS ' /' HSI ' Hue Saturation Luminance/Intensity' XYZ ' CIE XYZ' Lab ' CIE L* a* b* (CIELAB)' Luv ' CIE L* u* v* (CIELUV)' Lch ' CIE L* ch (CIE Platform: |
Size: 4096 |
Author:张灯结 |
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Description: 已知两个不同图像块亮度数据如下：
（1）分析DCT原理，采用DCT方法，编程并计算相应的DCT系数，分析系数分布特点。
（2）依据视觉特性分析量化表步长的分布特点，完成DCT系数量化。
（3）采用Z形扫描，实现输出数据的统计编码，形成Video stream。
（4）采用IDCT重建图像亮度数据，计算SAD大小，分析产生误差的原因及采用DCT进行数据压缩的原理。（ ）
（5）分别利用左上角1、3、6个系数重建图像，计算相应的SAD，并由此分析直流和低频系数的重要性。
-Known brightness of two different image data block is as follows: (1) Principles of analysis of DCT, the DCT method, program and calculate the corresponding DCT coefficient, analysis of distribution coefficients. (2) quantitative analysis based on visual characteristics of the distribution of long-form features step-by-step to complete the DCT coefficient quantization. (3) the use of Z-scan output data to achieve statistical encoding, the formation of Video stream. (4) the use of the reconstructed image brightness IDCT data to calculate the SAD size, analysis of the causes of errors and the use of DCT for the principle of data compression. () (5), respectively, a factor of 1,3,6 using the upper left corner of the reconstruction of images, calculating the corresponding SAD, and the resulting analysis of DC and the importance of low-frequency coefficients. Platform: |
Size: 1024 |
Author:张元 |
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Description: 图像的二值化处理就是讲图像上的点的灰度置为0或255，也就是讲整个图像呈现出明显的黑白效果。即将256个亮度等级的灰度图像通过适当的阀值选取而获得仍然可以反映图像整体和局部特征的二值化图像。-Binary image processing is to say the point of image gray-scale home for 0 or 255, that is, speaking of the images clearly show the effect of black and white. Brightness is about 256 levels of gray-scale image through appropriate threshold can be selected to reflect the characteristics of the overall and partial image of the binary image. Platform: |
Size: 3072 |
Author:zhangyun |
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Description: This paper provides an algorithm for partitioning grayscale images into disjoint regions of coherent
brightness and texture. Natural images contain both textured and untextured regions, so the cues of contour and
texture differences are exploited simultaneously. Contours are treated in the intervening contour framework, while
texture is analyzed using textons. Each of these cues has a domain of applicability, so to facilitate cue combination we
introduce a gating operator based on the texturedness of the neighborhood at a pixel. Having obtained a local measure
of how likely two nearby pixels are to belong to the same region, we use the spectral graph theoretic framework of
normalized cuts to find partitions of the image into regions of coherent texture and brightness. Experimental results
on a wide range of images are shown. Platform: |
Size: 159744 |
Author:aan |
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Description: The provided Matlab functions demonstrate a simple method for training and testing a color detection system. In general, a color detection algorithm searches an image for pixels that have a specific color. In this demo the HSV color space has been used, instead of the RGB space. According to that model, H(ue) dimension represents the "color", S(aturation) dimension represents the dominance of that color and the V(alue) dimension represents the brightness. Therefore, the color detection algorithm can search in terms of color position and color "purity", instead of searching for specific RGB values. We have to note here, that in order to detect the desired color, it is needed to define a tolerance in each HSV dimension. For example a tolerance equal to 0.050 in the H dimension means that the algorithm will detect pixels whose H value has a distance (from the desired value) less than 0.050. Platform: |
Size: 169984 |
Author:jack |
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Description: 直方图及直方图均衡化，用来增加许多图像的局部对比度，尤其是当图像的有用数据的对比度相当接近的时候。通过这种方法，亮度可以更好地在直方图上分布。这样就可以用于增强局部的对比度而不影响整体的对比度，直方图均衡化通过有效地扩展常用的亮度来实现这种功能。
-Used to increase the local contrast of many images, especially when the contrast of the image of the useful data is very close to the time. In this way, the brightness could be better distributed on the histogram. This can be used to enhance the local contrast without affecting the overall contrast, histogram equalization, by effectively expanding the brightness used to achieve this functionality. Platform: |
Size: 1024 |
Author:李洁琼 |
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Description: Load test (black) video in Matlab and export the
information on the brightness of individual images.-Load test (black) video in Matlab and export the
information on the brightness of individual images. Platform: |
Size: 1024 |
Author:Luke |
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Description: 分析图像，使用pixval函数来获得牌照的背景色的亮度值和坐标；通过统计的算法找出车牌的范围；通过修剪得到最终图像。-Analysis of images, a function to obtain a license to use pixval background color brightness values and coordinates through statistical algorithms to identify the scope of the license plate by trimming the final image. Platform: |
Size: 2048 |
Author:zhangping |
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Description: 根据matlab中的imadjust函数编写的程序，可以实现对彩色图像的亮度变换，参数要自己调一下-According to the function in matlab imadjust written procedures, can change the brightness of the color images, what parameters to tune their own Platform: |
Size: 8536064 |
Author:李芳 |
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Search - brightness in matlab