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Image Filtering

Image Filtering. Dr. Jane Dong Serenade Training Session Summer, 2004. Outline. Concept of image filter Focus on spatial image filter Various types of image filter Smoothing, noise reductions Sharpening Edge detection Implementations . What is spatial image filter.

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Image Filtering

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  1. Image Filtering Dr. Jane Dong Serenade Training Session Summer, 2004

  2. Outline • Concept of image filter • Focus on spatial image filter • Various types of image filter • Smoothing, noise reductions • Sharpening • Edge detection • Implementations

  3. What is spatial image filter • Image filter is an N*M operator, with center at w(0,0) • w(i, j) is coefficient 3x3 image filter

  4. Image filtering (1) •  A typical spatial filtering process is as follows • Move the filter from point to point in an image • At each point (x,y), calculate the response of the filter • Response of filtering is calculated by convolution

  5. Image filtering (2) • Convolution includes three steps: • Position the center of the filter at the first pixel of an image and flip the filter. • Calculate the inner product between the filter and the sub-image covered by the filter. • Slide to next pixel, repeat steps 2 and 3 until the whole image is processed

  6. Lowpass filtering (1) • Low pass image filters are used in image smoothing • Reduce noise • Image may become blurred • Example: • Average filter • Guassian filter

  7. Lowpass filtering (2) • Average filter: • Gaussian filter: 1/9 * 2-D Continuous Gaussian filter 1/16 *

  8. Example of smoothing

  9. Median Filter • Median filtering is to replace each pixel value in an image by the median of its neighborhood • Procedure of Median filtering (filter size nxm): • Sort the pixel values in the nxm sub-image, centered at (x,y), to find the median; • Replace the pixel value f(x,y) by the median.

  10. Gaussian vs. Median Gaussian Median ( 5 X 5) Source

  11. Edge detection (1) • Highpass filtering is used to sharpen the image or detect the edges • What is edge? • Gray level discontinuity • An important concept related to edge detection -- Gradient

  12. Edge detection (2) • Gradient is defined as a vector • Gradient reflects the degree of change of gray levels in x and y directions • An edge is detected if the gradient is larger than a threshold

  13. 1st order digital edge detector Robert’s operator Prewitt’s operator Sobel’s operator

  14. 2nd order edge detector • Also called Laplacian filter • Several variations of Laplacian filters exists (see textbook)

  15. An example of edge detection

  16. How to implement image filtering in MATLAB? • Refer to the examples in course website • Lowpass filtering (average filter) • Highpass filtering (Sobel filter) • Get familiar with block processing in MATLAB

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