Image processing Common problems and treatment methods

table of Contents

Image to dry

Image Enhancement

Image segmentation

Edge detection

Target Recognition

Goal Tracking

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Image Denoising

1. Spatial domain filtering
   1. Gaussian filter
   2. Median filter
2. Frequency domain filtering

Image Enhancement

1.  Histogram equalization

2. Laplacian

3. Log

4. Gamma

Image segmentation

1. Threshold-based segmentation
   1. Fixed Thresholding
   2. Bimodal histogram method
   3. OTSU
2. Segmentation Based on Edge
3. Based on the divided regions
   1. Regional growth
   2. Split and merge
   3. Watershed
   4. Related Links: http://www.cnblogs.com/wangduo/p/5556903.html
4. Segmentation based on graph theory
   1. Normalized Cuts algorithm
   2. Graph Cuts算法，Grab Cuts
   3. Superpixel lattice algorithm
5. Segmentation based energy functional
6. Segmentation based on wavelet analysis
7. Segmentation based on neural network 
8. Segmentation based clustering analysis 

Edge detection

1.  Roberts
2.  Sobel
3.  Prewitt
4.  Laplacian
5.  Log/Marr
6.  Canny
7.  Kirsch
8.  Nevitt

 
Target recognition
target tracking