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Combining Morphological Operations

The following example uses a variety of morphological operations to remove bridges from a satellite image of New York waterways. Complete the following steps for a detailed description of the process.


Example Code
See removebridges.pro in the examples/doc/image subdirectory of the IDL installation directory for code that duplicates this example.

  1. Prepare the display device and load a color table:
    2. DEVICE, DECOMPOSED = 0, RETAIN = 2  
LOADCT, 0

     

  2. Specify the known dimensions and use READ_BINARY to load the image:
    3. xsize = 768   
ysize = 512   
img = READ_BINARY(FILEPATH('nyny.dat', $  
   SUBDIRECTORY = ['examples', 'data']), $  
    DATA_DIMS = [xsize, ysize])

     

  3. Increase the image's contrast and display the image:
    4. img = BYTSCL(img)  
WINDOW, 1, TITLE = 'Original Image'  
TVSCL, img

     

    Figure 9-24: Original Image

    Figure 9-24: Original Image

     

  4. Prepare to threshold the image, using an intensity histogram as a guide for determining the intensity value:
    5. WINDOW, 4, XSIZE = 400, YSIZE = 300  
PLOT, HISTOGRAM(img)


Note
Using an intensity histogram as a guide for determining threshold values is described in the section, Determining Intensity Values for Threshold and Stretch.

  1. Create a mask of the darker pixels that have values less than 70:
    2. maskImg = img LT 70

     

  2. Define and create a small square structuring element, which has a shape similar to the bridges which will be masked out: 
    3. side = 3  
strucElem = DIST(side) LE side

     

  3. Remove details in the binary mask's shape by applying the opening operation:
    4. maskImg = MORPH_OPEN(maskImg, strucElem)

     

  4. Fuse gaps in the mask's shape by applying the closing operation and display the image:
    5. maskImg = MORPH_CLOSE(maskImg, strucElem)  
WINDOW, 1, title='Mask After Opening and Closing'  
TVSCL, maskImg

     

    This results in the following figure:

     

    Figure 9-25: Image Mask After Opening and Closing Operations

    Figure 9-25: Image Mask After Opening and Closing Operations

     

  5. Prepare to remove all but the largest region in the mask by labeling the regions:
    6. labelImg = LABEL_REGION(maskImg)

     

  6. Discard the black background by keeping only the white areas of the previous figure: 
    7. regions = labelImg[WHERE(labelImg NE 0)]

     

  7. Define mainRegion as the area where the population of the labelImg region matches the region with the largest population:
    8. mainRegion = WHERE(HISTOGRAM(labelImg) EQ $  
   MAX(HISTOGRAM(regions)))

     

  8. Define maskImg as the area of labelImg equal to the largest region of mainRegion, having an index number of 0 and display the image:
    9. maskImg = labelImg EQ mainRegion[0]  
Window, 3, TITLE = 'Final Masked Image'  
TVSCL, maskImg

     

    This results in a mask of the largest region, the waterways, as shown in the following figure.

     

    Figure 9-26: Final Image Mask

    Figure 9-26: Final Image Mask

     

  9. Remove noise and smooth contours in the original image:
    10. newImg = MORPH_OPEN(img, strucElem, /GRAY)

     

  10. Replace the new image with the original image, where it's not masked:
    11. newImg[WHERE(maskImg EQ 0)] = img[WHERE(maskImg EQ 0)]

     

  11. View the results using FLICK to alternate the display between the original image and the new image containing the masked areas: 
    12. WINDOW, 0, XSIZE = xsize, YSIZE = ysize  
FLICK, img, newImg

     

    Hit any key to stop the image from flickering. Details of the two images are shown in the following figure.

     

    Figure 9-27: Details of Original (left) and Resulting Image of New York (right)

    Figure 9-27: Details of Original (left) and Resulting Image of New York (right)

  IDL Online Help (March 06, 2007)