JHV User's Guide
Image Processing
JHV does a number of standard image processing algorithms. The image processing computation may take a long time to complete, depending on the size of the image and the speed of the computer. The image processing algorithms are selected from the menu options, which include color modification, palette edit, filter and contour.
1. Image Menu
The image menu is designed for modifying data range, changing image RGB balance, and setting image brightness.
- Range Modification changes the range of data set. Users may specify the maximum and minimum values to be displayed. Values outside of the range are set (pinned) to the nearer of the range bounds. Changing the data range changes the color of the image. The following is an example of range modification of a SDS data. The original data range is [202, 21412] and the modified range is [2092, 14692].
- RGB Balance lets users change the balance of red, green and blue color channels for the current image. The RGB balance panel looks like,
- Brightness/Contrast Controls let users change the image brightness and contrast. The brightness/Contrast panel looks like,
2. Filter Menu
The Image Transformation (filtering) includes several image-processing algorithms. These features are adapted from the popular `xv' utility.
- Smooth algorithm runs a convolution over each plane (r,g,b) of the image, using an n*n convolution mask consisting of all 1's. This
has the effect of replacing each pixel with the average value of all the pixels in the n*n rectangle centered around the pixel in question. Generally the resulting image is ``smooth'', with noise and small features averaged out.
- Sharpen option runs an edge-sharpening algorithm on the image, which attempts to maximize contrast between adjacent pixels. This highlights edges, lines, and borders.
- Add Noise algorithm adds or subtracts a small random amount
from each pixel in the image.
- Find Edge algorithm runs a convolution using a pair of convolutions,
one which detects horizontal edges, and one for vertical edges.
- Flip algorithm flips the image horizontally or vertically.
- Emboss algorithm produces a pseudo-3D 'embossed' effect by using a variation of the edge detection algorithm.
- Polarized image is generated by a polar interpretation of the row and column scaling information. The row scale is treated as a set of radius, and the column scale as a set of angle values in the range 0 to 2*PI radians.
3. Contour Menu
The Contour selection creates a contour plot for the image. The contour lines are drawn in 3, 5, or 9 levels, which are equally spaced in the range of the data. The following figure is an example of image contour. The left side is the original image, and the right side is the image contour with contour level 5.

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University of Illinois at Urbana-Champaign
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