Location:
Search - lenna.bmp
Search list
Description: digital image processing- lenna.bmp
Platform: |
Size: 164864 |
Author: gosling |
Hits:
Description: image_smooth.m ： 图像平滑主函数，调用average_median
average_median.m : 空域邻域平均法和中值滤波法对图像进行平滑处理
image_inhance.m : 图像增强主函数，调用inhance
inhance.m : 图像增强处理
lenna.bmp
woman_v7_5.bmp : 原始灰度图片
实验结果文件夹 ： 保存了实验过程中生成的图像和程序流程图-image_smooth.m: image smoothing the main function, call average_median average_median.m: spatial neighborhood average and median filtering method of image smoothing image_inhance.m: image enhancement main function, call inhance inhance.m: image enhancement lenna. bmp woman_v7_5.bmp: original gray-scale image results folder: Save the images generated during the experiment and the program flow chart
Platform: |
Size: 1341440 |
Author: 许胜强 |
Hits:
Description: edge_detect.m : 图像边缘检测
其中使用
梯度算子边缘检测 : roberts算子、prewitt算子、Sobel算子、Canny算子
二阶微分算子法 : 拉普拉斯高斯算子、canny算子
lenna.bmp : 原始灰度图片
实验结果文件夹 ： 保存了实验过程中生成的图像和程序流程图-edge_detect.m: edge detection which uses the gradient operator edge detection: roberts operator, prewitt operator, Sobel operator, Canny operator second-order differential operator method: Laplacian Gaussian operator, canny operator lenna . bmp: original gray image results folder: Save the images generated during the experiment and the program flow chart
Platform: |
Size: 389120 |
Author: 许胜强 |
Hits:
Description: image_binaryzation.m : 图像二值化主函数，调用otsu、kittler
otsu.m : 类判别分类法（otsu全局二值化算法）
kittler : 最小分类错误(minimum error thresholding)全局二值化算法
image_refining.m : 图像细化主程序，调用otsu、refining
refining.m : 计算骨架的一种实用方法对图像进行细化
coins.bmp
lenna.bmp
woman_v7_5.bmp : 原始灰度图片
实验结果文件夹 ： 保存了实验过程中生成的图像和程序流程图-image_binaryzation.m: image binarization main function, call otsu, kittler otsu.m: class discriminant classification (otsu global binarization algorithm) kittler: minimum classification error (minimum error thresholding) global binarization algorithm image_refining.m: thinning the main program, call otsu, refining refining.m: a practical method of calculating the skeleton of the image refinement coins.bmp lenna.bmp woman_v7_5.bmp: original gray-scale image results folder: Save the experiment generated images and the program flow chart
Platform: |
Size: 721920 |
Author: 许胜强 |
Hits:
Description: 這一個“慢”，但簡單和兩維FFT的演示可以從這裡下載（包括源）。
演示生成的一維或二維的輸入信號（256或256×256大小），這是顯示在左邊的位圖（8位灰度調色板）。
信號包含一個中心的矩形脈衝（脈衝大小從2到256）。因為輸入的是真實的，FFT的日常工聯會（）產生偏見的頻譜。如果“重排”被選中，零頻率頻譜的中心轉移到從各自的象限交換數據。複雜的結果顯示在正確的位圖，在可能的方式有四種：模塊，相位，實部或虛部。如果“InvFFT”被選中，逆FFT頻譜，結果是恢復輸入信號應用。然而，恢復輸入信號正確的“重新排序”，已是自由。為了保持傳統的2D信號可以餵從演示Lenna.bmp文件。 （Lenna見下面）。-This "slow" but simple One- and Two-dimensional FFT Demo can be downloaded from here (source included).
The Demo generates a 1D or 2D input signal (with size 256 or 256x256) which is displayed in the left bitmap (8 bit gray palette).
The signal contains a centered rectangular pulse (pulse size from 2 to 256). Since the input is real, the FFT routine ftu() produces biased spectrum. If "Reorder" is checked, the zero frequency is shifted to the center of the spectrum by swapping data from the respective quadrants. The complex result is displayed in the right bitmap in one of four possible modes: Module, Phase, Real part or Imaginary part. If "InvFFT" is checked, an inverse FFT is applied on the spectrum, the result being the recovered input signal. However, to recover the input signal correctly "Reorder" has to be unchecked. In order to keep up with tradition, the 2D signal may be fed from Lenna.bmp file which comes with the Demo. (See about Lenna below).
Platform: |
Size: 302080 |
Author: 蕭柏堂 |
Hits:
