![]() ![]() You just scaled up a portion of a large image, but it's more common to need to scale down large images to a size that's more workable. Scaling images that are too big to work with Close all of the open image and stack windows.The size of the mini-stack is 24K and the size of the scaled stack is 2460K —indeed, 100 times larger. (Conversely, scaling by 0.5 decreases the size of the image 0.5 2 times, or 25% (1/4) its original size. Doubling the scale increases the size of the image by 2 2 or 4 times. In other words, the size (memory) of the image increases by the square of the scaling factor. Since you scaled BOTH the height and width of the image by 10x, the area (or number of pixels, or the memory size) of the image is 10 x 10 = 100 times as large as the original. Look at the memory size of the mini-stack and the file size of the 10x stacks (Tip: The memory size of each open image window is displayed at the bottom of the Window menu.(If not, try the process again on one of the other 10x images you created.) Measure the diameter of the crater you just re-calibrated.This would be a good time to turn off the global setting. Activate any one of the 10x images and choose Analyze / Set Scale and change the scale to 3 meters per pixel.The new spatial calibration is 30/10 or 3 meters/pixel. (Tip: To select a perfect square centered on the crater, hold down Command-Shift (Mac) or Control-Shift (PC), click at the center of the crater, and drag outward.) Since the scale is set at 30m per pixel, 60 pixels equals 60 x 30 = 1800 meters. The selection size appears in the image status bar as you make the selection. Use the rectangular selection tool to select a 60 x 60 pixel square centered on the crater.Activate the stack window, locate the crater, and zoom in until the crater fills most of the window.If necessary, set the spatial scale of the image to 30m/pixel. ![]() To compare interpolation methods, you will crop out a small image of the crater, then scale it up by a factor of 10 using each method. This is not an issue with today's powerful computers. Bilinear interpolation is generally faster, while bicubic interpolation is more complex and takes a bit longer. Without going into the detailed mathematics of the different interpolation methods, you do need to know that the Interpolation method (bilinear, bicubic, or none) is most important if you're scaling images up to a larger size (scale > 1), but usually won't make much difference when you're scaling down, especially at "even" scales like 25% or 50%. Scaling is the process of making an image larger (scale > 1.0) or smaller (scale interpolation. Scaling, Interpolation, and Spatial Calibration What if these images were too large to work with, either for you or for your students? What could you do? Two common solutions are scaling the images down and cropping them to a smaller size. Part 2: Scale and Crop Images 3 Scaling and Cropping Images and Stacks ![]()
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