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CCD Image Processing: Issues & Solutions

CCD Image Processing: Issues & Solutions. CCDs: noise sources. dark current signal from unexposed CCD read noise uncertainty in counting electrons in pixels sky “background” diffuse light from bright sky (usually variable) photon counting

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CCD Image Processing: Issues & Solutions

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  1. CCD Image Processing:Issues & Solutions

  2. CCDs: noise sources • dark current • signal from unexposed CCD • read noise • uncertainty in counting electrons in pixels • sky “background” • diffuse light from bright sky (usually variable) • photon counting • intrinsic uncertainties in reliably counting incoming photons

  3. Dark Current • Issue: CCD produces signal in every pixel whether or not it’s exposed to light • signal strength is proportional to time • Solution: subtract image(s) obtained without exposing CCD • leave CCD covered: dark frame • match dark frame exposure time to source exp. time • obtain multiple images, to decrease uncertainty in dark current

  4. Read Noise • Issue: detector electronics subject to uncertainty in reading out the number of electrons in each pixel • Solution: collect enough photons that read noise is less important than photon counting noise • Some CCD-like devices enable “nondestructive readout” of detector pixels • CIDs: “charge injection devices” (used for IR work) • multiple reads of CID pixels reduces uncertainty

  5. Background Sky • Issue: signal from (possibly variable) bright sky introduces source photon counting uncertainties • how much signal was from the source as opposed to the intervening atmosphere? • Solution: measure and subtract sky signal • obtain independent images of the sky • must be near source images in both time and space • use off-source region(s) of source image

  6. Photon Counting • Issue: counting of source photons is governed by Poisson statistics • if I detect N photons, the uncertainty in my photon count is root(N) • Solution: collect as many photons as possible! • uncertainty decreases like root(N) • so, maximize telescope collecting area (aperture) and exposure time so as to maximize source illumination of detector

  7. CCDs: artifacts and defects • bad pixels • dead, hot, flickering… • pixel-to-pixel differences in quantum efficiency • every CCD pixel has a unique QE • saturation • each pixel can only hold so much charge (limited well depth) • charge loss during pixel charge transfer & readout • a pixel’s value at readout may not be what it was when light was collected

  8. Bad Pixels • Issue: a certain fraction of a typical CCD’s pixels will be “dead” (never reporting any charge collected) or “hot” (always reporting more charge than actually collected) • Solutions: • replace bad pixel with average value of the pixel’s neighbors • dither telescope • take a series of images, move telescope slightly to ensure source(s) falls on good pixels • must then register and appropriately combine dithered images

  9. Pixel-to-Pixel Differences in QE • Issue: each pixel has its own response to light • Solution: obtain and use a flat field image to correct for pixel-to-pixel nonuniformities • construct flat field by exposing CCD to a uniform source of illumination • image the sky or a white screen pasted on the dome • divide source images by the flat field image • for every pixel x,y, new source intensity is now S’(x,y) = S(x,y)/F(x,y) where F(x,y) is the flat field pixel value; “bright” pixels are suppressed, “dim” pixels are emphasized

  10. Saturation • Issue: each pixel can only hold so much charge (limited well depth), so a bright source may saturate detector • at saturation, pixel stops detecting new photons (like overexposure) • saturated pixels can “bleed” over to neighbors, causing streaks in image • Solution: put less light on detector in each image • take shorter exposures and add them together • telescope pointing will drift; need to re-register images • read noise can become a problem • use neutral density filter • a filter that blocks some light at all wavelengths uniformly • fainter sources lost

  11. Charge Loss • Issue: no CCD transfers charge between pixels with 100% efficiency • charge loss introduces uncertainty in converting signal to light intensity (optical) or to photon energy (X-ray) • Solution: build a better CCD • most modern CCDs have charge transfer efficiencies of 99.9999% • some don’t, though (soft X-ray sensitive CCDs)

  12. Data Pipelining • Issue: now that I’ve collected all of these images, what do I do? • Solution: build an automated data processing pipeline • Space observatories (e.g., HST) routinely process raw image data and deliver only the processed images to the observer • ground-based observatories are slowly coming around to this operational model • RIT’s CIS is in the “data pipeline” business • NASA’s SOFIA • South Pole facilities

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