Photometry - 10/18/10 Photometry: Basic Questions How do...

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10/18/10 1 Basics of Photometry Photometry: Basic Questions How do you identify objects in your image? How do you measure the flux from an object? What are the potential challenges? Does it matter what type of object you’re studying?
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10/18/10 2 Topics 1. General Considerations 2. Stellar Photometry 3. Extended Source Photometry I: General Considerations 1. Garbage in, garbage out. .. 2. Object Detection 3. Centroiding 4. Measuring Flux 5. Background Flux 6. Computing the noise and correlated pixel statistics I: General Considerations Object Detection How do you mathematically define where there’s an object? I: General Considerations Object Detection Define a detection threshold and detection area . An object is only detected if it has N pixels above the threshold level. One simple example of a detection algorithm: Generate a segmentation image that includes only pixels above the threshold. Identify each group of contiguous pixels, and call it an object if there are more than N contiguous pixels
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10/18/10 3 I: General Considerations Object Detection Define a detection threshold and detection area . An object is only detected if it has N pixels above the threshold level. One simple example of a detection algorithm: Generate a segmentation image that includes only pixels above the threshold. Identify each group of contiguous pixels, and call it an object if there are more than N contiguous pixels I: General Considerations Object Detection Define a detection threshold and detection area . An object is only detected if it has N pixels above the threshold level. One simple example of a detection algorithm: Generate a segmentation image that includes only pixels above the threshold. Identify each group of contiguous pixels, and call it an object if there are more than N contiguous pixels I: General Considerations Object Detection I: General Considerations Object Detection
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10/18/10 4 Centroiding Centroiding How do you determine the centroid of an object? Consider an image with flux levels I(i,j) in pixel i,j. The marginal distribution along a given axis is obtained by extracting a subsection of the image and summing along the row or columns. Note that this is not the only way to find the centroid. Examples of marginal distributions. From Mike Bolte's lecture notes: http://www.ucolick.org/~bolte/AY257/ay257_2.pdf and Steve Majewski’s lecture notes: http://www.astro.virginia.edu/class/majewski/astr313/ lectures/photometry/photometry_methods.html Centroiding Centroiding: Marginal Distribution Step 1: Sum the pixel values I ij along the 2N+1 rows and columns around the object. These are the marginal distributions.
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Photometry - 10/18/10 Photometry: Basic Questions How do...

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