Comments on: Measuring Where Hubble Is http://granades.com/feeder/?FeederAction=clicked&feed=Comments+on+Articles+%28RSS2%29&seed=http%3A%2F%2Fgranades.com%2F2007%2F07%2F26%2Fmeasuring-where-hubble-is%2F%23comment-&seed_title=Measuring+Where+Hubble+Is Like a blog, but explodier Thu, 21 Aug 2008 19:26:27 +0000 http://wordpress.org/?v=2.6 By: Chris S. http://granades.com/feeder/?FeederAction=clicked&feed=Comments+on+Articles+%28RSS2%29&seed=http%3A%2F%2Fgranades.com%2F2007%2F07%2F26%2Fmeasuring-where-hubble-is%2F%23comment-55859&seed_title=Measuring+Where+Hubble+Is#comment-55859 Chris S. Fri, 27 Jul 2007 14:25:25 +0000 http://granades.com/2007/07/26/measuring-where-hubble-is/#comment-55859 Yea that makes since. Neat stuff, I never actually knew *what* you did nice to get an idea = ) Yea that makes since. Neat stuff, I never actually knew *what* you did nice to get an idea = )

]]> By: Stephen http://granades.com/feeder/?FeederAction=clicked&feed=Comments+on+Articles+%28RSS2%29&seed=http%3A%2F%2Fgranades.com%2F2007%2F07%2F26%2Fmeasuring-where-hubble-is%2F%23comment-55858&seed_title=Measuring+Where+Hubble+Is#comment-55858 Stephen Fri, 27 Jul 2007 14:19:53 +0000 http://granades.com/2007/07/26/measuring-where-hubble-is/#comment-55858 In our case, we're doing a two-dimensional fourier transform of the intensity of the image (like 0 to 255 greyscale). You perform the Fourier transform over the x and y axes and what you get out is a map of the frequency response along x and along y. Correlation, in the Fourier domain, involves multiplying two Fourier-transformed signals together. In this case we Fourier transform the image and compare it to various filters -- bits of reference images we've already Fourier transformed. If the bits of reference image appear somewhere in the first image, then we'll get a peak in the Fourier plane that corresponds to where the reference image is. In our case, we’re doing a two-dimensional fourier transform of the intensity of the image (like 0 to 255 greyscale). You perform the Fourier transform over the x and y axes and what you get out is a map of the frequency response along x and along y.

Correlation, in the Fourier domain, involves multiplying two Fourier-transformed signals together. In this case we Fourier transform the image and compare it to various filters — bits of reference images we’ve already Fourier transformed. If the bits of reference image appear somewhere in the first image, then we’ll get a peak in the Fourier plane that corresponds to where the reference image is.

]]> By: Chris S. http://granades.com/feeder/?FeederAction=clicked&feed=Comments+on+Articles+%28RSS2%29&seed=http%3A%2F%2Fgranades.com%2F2007%2F07%2F26%2Fmeasuring-where-hubble-is%2F%23comment-55857&seed_title=Measuring+Where+Hubble+Is#comment-55857 Chris S. Fri, 27 Jul 2007 13:01:41 +0000 http://granades.com/2007/07/26/measuring-where-hubble-is/#comment-55857 Hey that's cool stuff Stephen. So, I'm a bit curious. In RF I know what a Fourier Transform of a signal means. But, I'm not really sure how you take the F.T. of an image. Or what exactly that gives you. Does that involve looking at the luminance of the image? The color map? Some combination of it? Hey that’s cool stuff Stephen. So, I’m a bit curious. In RF I know what a Fourier Transform of a signal means. But, I’m not really sure how you take the F.T. of an image. Or what exactly that gives you. Does that involve looking at the luminance of the image? The color map? Some combination of it?

]]>