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Activity 2 : Use of CCD Cameras. Simon Tulloch [email protected] iac. es In this activity some of the practical considerations of using and building CCD cameras are described. Nik Szymanek
Spectral Sensitivity of CCDs Transmission of Atmosphere The graph below shows the transmission of the atmosphere when looking at objects at the zenith. The atmosphere absorbs strongly below about 330 nm, in the near ultraviolet part of the spectrum. An ideal CCD should have a good sensitivity from 330 nm to approximately 1000 nm, at which point silicon, from which CCDs are manufactured, becomes transparent and therefore insensitive. Wavelength (Nanometers) Over the last 25 years of development, the sensitivity of CCDs has improved enormously, to the point where almost all of the incident photons across the visible spectrum are detected. CCD sensitivity has been improved using two main techniques : ‘thinning’ and the use of anti-reflection coatings. These are now explained in more detail.
Incoming photons Thick Front-side Illuminated CCD p-type silicon n-type silicon 625 mm Silicon dioxide insulating layer Polysilicon electrodes These are cheap to produce using conventional wafer fabrication techniques. They are used in consumer imaging applications. Even though not all the photons are detected, these devices are still more sensitive than photographic film. They have a low Quantum Efficiency due to the reflection and absorption of light in the surface electrodes. Very poor blue response. The electrode structure prevents the use of an Anti-reflective coating that would otherwise boost performance. The amateur astronomer on a limited budget might consider using thick CCDs. For professional observatories, the economies of running a large facility demand that the detectors be as sensitive as possible; thick front-side illuminated chips are seldom if ever used.
Anti-Reflection Coatings 1 Silicon has a very high Refractive Index (denoted by n). This means that photons are strongly reflected from its surface. ni nt Fraction of photons reflected at the interface between two mediums of differing refractive indices = [ nt-ni nt+ni ] 2 n of air or vacuum is 1. 0, glass is 1. 46, water is 1. 33, Silicon is 3. 6. Using the above equation we can show that window glass in air reflects 3. 5% and silicon in air reflects 32%. Unless we take steps to eliminate this reflected portion, then a silicon CCD will at best only detect 2 out of every 3 photons. The solution is to deposit a thin layer of a transparent dielectric material on the surface of the CCD. The refractive index of this material should be between that of silicon and air, and it should have an optical thickness = 1/4 wavelength of light. The question now is what wavelength should we choose, since we are interested in a wide range of colours. Typically 550 nm is chosen, which is close to the middle of the optical spectrum.
Anti-Reflection Coatings 2 With an Anti-reflective coating we now have three mediums to consider : ni ns nt Air AR Coating Silicon The reflected portion is now reduced to : In the case where [ nt x ni-ns 2 nt x ni+ns 2 ] 2 n 2= nt the reflectivity actually falls to zero! For silicon we require a material s with n = 1. 9, fortunately such a material exists, it is Hafnium Dioxide. It is regularly used to coat astronomical CCDs.
Anti-Reflection Coatings 3 The graph below shows the reflectivity of an EEV 42 -80 CCD. These thinned CCDs were designed for a maximum blue response and it has an anti-reflective coating optimised to work at 400 nm. At this wavelength the reflectivity falls to approximately 1%.
Incoming photons Thinned Back-side Illuminated CCD 15 mm Anti-reflective (AR) coating p-type silicon n-type silicon Silicon dioxide insulating layer Polysilicon electrodes The silicon is chemically etched and polished down to a thickness of about 15 microns. Light enters from the rear and so the electrodes do not obstruct the photons. The QE can approach 100%. These are very expensive to produce since thinning is a non-standard process that reduces the chip yield. These thinned CCDs become transparent to near infra-red light and the red response is poor. Response can be boosted by the application of an anti-reflective coating on the thinned rear-side. These coatings do not work so well for thick CCDs due to the surface bumps created by the surface electrodes. Almost all Astronomical CCDs are Thinned and Backside Illuminated.
Quantum Efficiency Comparison The graph below compares the quantum of efficiency of a thick frontside illuminated CCD and a thin backside illuminated CCD.
‘Internal’ Quantum Efficiency If we take into account the reflectivity losses at the surface of a CCD we can produce a graph showing the ‘internal QE’ : the fraction of the photons that enter the CCDs bulk that actually produce a detected photo-electron. This fraction is remarkably high for a thinned CCD. For the EEV 42 -80 CCD, shown below, it is greater than 85% across the full visible spectrum. Todays CCDs are very close to being ideal visible light detectors!
Appearance of CCDs The fine surface electrode structure of a thick CCD is clearly visible as a multi-coloured interference pattern. Thinned Backside Illuminated CCDs have a much planer surface appearance. The other notable distinction is the two-fold (at least) price difference. Kodak Kaf 1401 Thick CCD MIT/LL CC 1 D 20 Thinned CCD
Computer Requirements 1. Computers are required firstly to coordinate the sequence of clock signals that need to be sent to a CCD and its signal processing electronics during the readout phase, but also for data collection and the subsequent processing of the images. The CCD Controller In this first application, the computer is an embedded system running in a ‘CCD controller’. This controller will typically contain a low noise analogue section for amplification and filtering of the CCD video waveform, an analogue to digital converter, a high speed processor for clock waveform generation and a fibre optic transceiver for receipt of commands and transmission of pixel data. An astronomical system might require clock signals to be generated with time resolutions of a few tens of nanoseconds. This is typically done using Digital Signal Processing (DSP) chips running at 50 Mhz. Clock sequences are generated in software and output from the DSP by way of on-chip parallel ports. The most basic CCD design requires a minimum of 7 clock signals. Perhaps 5 more are required to coordinate the operation of the signal processing electronics. DSPs also contain several on-chip serial ports which can be used to transmit pixel data at very high rates. DSPs come with a small on-chip memory for the storage of waveform generation tables and software. Less time critical code , such as routines to initialise the camera and interpret commands can be stored in a few KB of external RAM. The computer running in the CCD controller is thus fast and of relatively simple design. A poorly performing processor here could result in slow read out times and poor use of telescope resources. Remember that when a CCD is reading out the telescope shutter is closed and no observations are possible. For an amateur observer using a small CCD with a fast readout time, a slow CCD controller may not be such a disadvantage; there are not so many pixels to process.
Computer Requirements 2. The Data Acquisition System(DAS) This will be typically based around a SUN SPARC workstation which is a high-end desktop computer. Pixel data will be received from the CCD controller by way of a fibre optic. The hardware in such a system will be cheap and ‘off-the shelf’, the only speciality item being the high speed fibre optic transceiver card. The hardware may typically consist of a Sparc Ultra 6 workstation, 500 Mb of RAM, a 9 GB hard-drive and a DAT drive. There will also be a high speed Ethernet card for connection to the observatory Local Area Network. The software required to carry out the data acquisition task is typically developed in-house by each observatory and represents the major cost of such a system. It will provide an easy-to-use interface (typically graphics based) between observer and instrument. Its complexity will be further increased by the need to talk to other telescope systems such as the Telescope Control System. This will allow information on the pointing of the telescope to be stored alongside the pixel data as a ‘file header’.
Computer Requirements 3. Image Processing Computers These are used for reduction and analysis of the astronomical data. Many astronomers process their data in real-time, i. e. they may be analysing one exposure whilst the next exposure is actually been taken. Others will take a cursory look at their data in real time but leave the heavy image processing tasks for when they return to their home institution. With large mosaic cameras producing very large data files, a high end system is required. A typical system would be : PC with a 1 GHz CPU A Enough RAM for at least 2 images , using 4 bytes per pixel (for a mosaic camera this could run to 500 MBytes) least 100 GBytes (300 GBytes would be better) of local hard disc space At If we use such a system to analyse images from a four chip CCD mosaic containing 36 Million pixels, the following performance would be obtained : Linearisation, bias subtraction and flat-fielding : ~150 sec de-fringing : ~300 sec object detection and star/galaxy separation : ~300 sec
Computer Requirements 4. Image Processing Computers (Contd. ) This professional system is unusual in its high demands on disc space and RAM. The processor speed , however, is the same as that found in current PCs costing a few thousand dollars. An amateur observer with a small 1 K square CCD camera will find a medium level PC quite sufficient for operation of the camera and for image processing. The system specs would typically be: Pentium III 500 MHz processor, MB RAM 256 MB video memory 32 30 GB Hard Drive Writer CD 19” monitor (twin monitors are even better, one for images , one for text) a For operation of the camera the bottleneck is often the data transfer between camera and PC. For image processing applications such as Maximum Entropy or Lucy-Richardson de-convolution (a form of image sharpening), a high speed PC is needed.
Blooming in a CCD 1. The charge capacity of a CCD pixel is limited, when a pixel is full the charge starts to leak into adjacent pixels. This process is known as ‘Blooming’. pixel boundary Photons pixel boundary Overflowing charge packet Spillage Photons Spillage
Blooming in a CCD 2. The diagram shows one column of a CCD with an over-exposed stellar image focused on one pixel. The channel stops shown in yellow prevent the charge spreading sideways. The charge confinement provided by the electrodes is less so the charge spreads vertically up and down a column. The capacity of a CCD pixel is known as the ‘Full Well’. It is dependent on the physical area of the pixel. For Tektronix CCDs, with pixels measuring 24 mm x 24 mm it can be as much as 300, 000 electrons. Bloomed images will be seen particularly on nights of good seeing where stellar images are more compact. Flow of bloomed charge In reality, blooming is not a big problem for professional astronomy. For those interested in pictorial work, however, it can be a nuisance.
Blooming in a CCD 3. The image below shows an extended source with bright embedded stars. Due to the long exposure required to bring out the nebulosity, the stellar images are highly overexposed and create bloomed images. M 42 Bloomed star images (The image is from a CCD mosaic and the black strip down the center is the space between adjacent detectors)
Image Defects in a CCD 1. Unless one pays a huge amount it is generally difficult to obtain a CCD free of image defects. The first kind of defect is a ‘dark column’. Their locations are identified from flat field exposures. Dark columns are caused by ‘traps’ that block the vertical transfer of charge during image readout. The CCD shown at left has at least 7 dark columns, some grouped together in adjacent clusters. Traps can be caused by crystal boundaries in the silicon of the CCD or by manufacturing defects. Although they spoil the chip cosmetically, dark columns are not a big problem for astronomers. This chip has 2048 image columns so 7 bad columns represents a tiny loss of data. Flat field exposure of an EEV 42 -80 CCD
Image Defects in a CCD 2. There are three other common image defect types : Cosmic rays, Bright columns and Hot Spots. Their locations are shown in the image below which is a lengthy exposure taken in the dark (a ‘Dark Frame’) Bright Column Cluster of Hot Spots Cosmic rays Bright columns are also caused by traps. Electrons contained in such traps can leak out during readout causing a vertical streak. Hot Spots are pixels with higher than normal dark current. Their brightness increases linearly with exposure times Cosmic rays are unavoidable. Charged particles from space or from radioactive traces in the material of the camera can cause ionisation in the silicon. The electrons produced are indistinguishable from photo-generated electrons. Approximately 2 cosmic rays per cm 2 per minute will be seen. A typical event will be spread over a few adjacent pixels and contain several thousand electrons. Somewhat rarer are light-emitting defects which are hot spots that act as tiny LEDS and cause a halo of light on the chip. 900 s dark exposure of an EEV 42 -80 CCD
Image Defects in a CCD 3. Some defects can arise from the processing electronics. This negative image has a bright line in the first image row. M 51 Dark column Hot spots and bright columns Bright first image row caused by incorrect operation of signal processing electronics.
Biases, Flat Fields and Dark Frames 1. These are three types of calibration exposures that must be taken with a scientific CCD camera, generally before and after each observing session. They are stored alongside the science images and combined with them during image processing. These calibration exposures allow us to compensate for certain imperfections in the CCD. As much care needs to be exercised in obtaining these images as for the actual scientific exposures. Applying low quality flat fields and bias frames to scientific data can degrade rather than improve its quality. Bias Frames A bias frame is an exposure of zero duration taken with the camera shutter closed. It represents the zero point or base-line signal from the CCD. Rather than being completely flat and featureless the bias frame may contain some structure. Any bright image defects in the CCD will of course show up, there may be also slight gradients in the image caused by limitations in the signal processing electronics of the camera. It is normal to take about 5 bias frames before a night’s observing. These are then combined using an image processing algorithm that averages the images, pixel by pixel, rejecting any pixel values that are appreciably different from the other 4. This can happen if a pixel in one bias frame is affected by a cosmic ray event. It is unlikely that the same pixel in the other 4 frames would be similarly affected so the resultant ‘master bias’, should be uncontaminated by cosmic rays. Taking a number of biases and then averaging them also reduces the amount of noise in the bias images. Averaging 5 frames will reduce the amount of read noise (electronic noise from the CCD amplifier) in the image by the square-root of 5.
Biases, Flat Fields and Dark Frames 2. Flat Fields Some pixels in a CCD will be more sensitive than others. In addition there may be dust spots on the surface of either the chip, the window of the camera or the coloured filters mounted in front of the camera. A star focused onto one part of a chip may therefore produce a lower signal than it might do elsewhere. These variations in sensitivity across the surface of the CCD must be calibrated out or they will add noise to the image. The way to do this is to take a ‘flat-field ‘ image : an image in which the CCD is evenly illuminated with light. Dividing the science image , pixel by pixel , by a flat field image will remove these sensitivity variations very effectively. Since some of these variations are caused by shadowing from dust spots, it is important that the flat fields are taken shortly before or after the science exposures; the dust may move around! As with biases, it is normal to take several flat field frames and average them to produce a ‘Master’. A flat field is taken by pointing the telescope at an extended , evenly illuminated source. The twilight sky or the inside of the telescope dome are the usual choices. An exposure time is chosen that gives pixel values about halfway to their saturation level i. e. a medium level exposure. Dark Frames. Dark current is generally absent from professional cameras since they are operated cold using liquid nitrogen as a coolant. Amateur systems running at higher temperatures will have some dark current and its effect must be minimised by obtaining ‘dark frames’ at the beginning of the observing run. These are exposures with the same duration as the science frames but taken with the camera shutter closed. These are later subtracted from the science frames. Again, it is normal to take several dark frames and combine them to form a Master, using a technique that rejects cosmic ray features.
Biases, Flat Fields and Dark Frames 3. A dark frame and a flat field from the same EEV 42 -80 CCD are shown below. The dark frame shows a number of bright defects on the chip. The flat field shows a criss-cross patterning on the chip created during manufacture and a slight loss of sensitivity in two corners of the image. Some dust spots are also visible. Dark Frame Flat Field
Biases, Flat Fields and Dark Frames 4. If there is significant dark current present, the various calibration and science frames are combined by the following series of subtractions and divisions : Science Frame Dark Frame Science -Dark Output Image Science -Dark Flat Field Image Flat-Bias Flat -Bias Image
Dark Frames and Flat Fields 5. In the absence of dark current, the process is slightly simpler : Science Frame Bias Image Science -Bias Output Image Science -Bias Flat Field Image Flat -Bias
Pixel Size and Binning 1. Nyquist Sampling It is important to match the size of a CCD pixel to the focal length of the telescope. Atmospheric seeing places a limit on the sharpness of an astronomical image for telescope apertures above 15 cm. Below this aperture, the images will be limited by diffraction effects in the optics. In excellent seeing conditions, a large telescope can produce stellar images with a diameter of 0. 6 arc-seconds. In order to record all the information present in such an image, two pixels must fit across the stellar image; the pixels must subtend at most 0. 3 arc-seconds on the sky. This is the ‘Nyquist criteria’. If the pixels are larger than 0. 3 arc-seconds the Nyquist criteria is not met, the image is under-sampled and information is lost. The Nyquist criteria also applies to the digitisation of audio waveforms. The audio bandwidth extends up to 20 KHz , so the Analogue to Digital Conversion rate needs to exceed 40 KHz for full reproduction of the waveform. Exceeding the Nyquist criteria leads to ‘over-sampling’. This has the disadvantage of wasting silicon area ; with improved matching of detector and optics a larger area of sky could be imaged. Under-sampling an image can produce some interesting effects. One of these is the introduction of features that are not actually present. This is occasionally seen in TV broadcasts when, for example, the fine-patterned shirt of an interviewee breaks up into psychedelic bands and ripples. In this example, the TV camera pixels are too big to record the fine detail present in the shirt. This effect is known as ‘aliasing’.
Pixel Size and Binning 2. Matching the Pixels to the telescope Example 1. The William Herschel Telescope, with a 4. 2 m diameter primary mirror and a focal ratio of 3 is to be used for prime focus imaging. What is the optimum pixel size assuming that the best seeing at the telescope site is 0. 7 arc-seconds ? First we calculate the ‘plate-scale’ in arc-seconds per millimeter at the focal plane of the telescope. Plate Scale (arc-seconds per mm) = 206265 =16. 4 arc-sec per mm Aperture in mm X f-number (Here the factor 206265 is the number of arc-seconds in a Radian ) Next we calculate the linear size at the telescope focal plane of a stellar image (in best seeing conditions) Linear size of stellar image = 0. 7 / Plate Scale = 0. 7/ 16. 4 = 42 microns. To satisfy the Nyquist criteria, the maximum pixel size is therefore 21 microns. In practice, the nearest pixel size available is 13. 5 microns which leads to a small degree of over-sampling.
Pixel Size and Binning 3. Example 2. An Amateur telescope with a 20 cm aperture and a focal ratio of 10 is to be used for imaging. The best seeing conditions at the observing site will be 1 arc-second. What is the largest pixel size that can be used? Plate Scale (arc-seconds per mm) = 206265 =103 arc-sec per mm Aperture in mm X f-number Linear size of stellar image = 1 / Plate Scale = 1/ 103 = 9. 7 microns. To satisfy the Nyquist criteria, the maximum pixel size is therefore 5 microns. This is about the lower limit of available pixel sizes.
Pixel Size and Binning 4. Binning In the first example we showed that with 13. 5 micron pixels the system exceeded the Nyquist Criteria even on nights with exceptionally good sub-arcsecond seeing. If we now suppose that the seeing is 2 arc-seconds, the size of a stellar image will increase to 120 microns on the detector. The image will now be grossly over-sampled. (One way to think of this is that the image is less sharp and therefore requires fewer pixels to record it). It would be more efficient now for the astronomer to switch to a detector with larger pixels since the resultant image files would be smaller, quicker to read out and would occupy less disc space. There is a way to read out a CCD so as to increase the effective pixel size, this is known as ‘Binning’. With binning we can increase pixel size arbitrarily. In the limit we could even read out the CCD as a single large pixel. Astronomers will more commonly use 2 x 2 binning which means that the charge in each 2 x 2 square of adjacent pixels is summed on the chip prior to delivery to the output amplifier. One important advantage of ‘on-chip binning’ is that it is a noise free process. Binning is done in two distinct stages : vertical binning and horizontal binning. Each may be done without the other to yield rectangular pixels.
Pixel Size and Binning 5. Stage 1 : Vertical Binning This is done by summing the charge in consecutive rows. The summing is done in the serial register. In the case of 2 x 2 binning, two image rows will be clocked consecutively into the serial register prior to the serial register being read out. We now go back to the conveyor belt analogy of a CCD. In the following animation we see the bottom two image rows being binned. Charge packets
Pixel Size and Binning 6. The first row is transferred into the serial register
Pixel Size and Binning 7. The serial register is kept stationary ready for the next row to be transferred.
Pixel Size and Binning 8. The second row is now transferred into the serial register.
Pixel Size and Binning 9. Each pixel in the serial register now contains the charge from two pixels in the image area. It is thus important that the serial register pixels have a higher charge capacity. This is achieved by giving them a larger physical size.
Pixel Size and Binning 10. Stage 2 : Horizontal Binning This is done by combining charge from consecutive pixels in the serial register on a special electrode positioned between serial register and the readout amplifier called the Summing Well (SW). The animation below shows the last two pixels in the serial register being binned : 1 2 3 SW Output Node
Pixel Size and Binning 11. Charge is clocked horizontally with the SW held at a positive potential. 1 2 3 SW Output Node
Pixel Size and Binning 12. 1 2 3 SW Output Node
Pixel Size and Binning 13. 1 2 3 SW Output Node
Pixel Size and Binning 14. The charge from the first pixel is now stored on the summing well. 1 2 3 SW Output Node
Pixel Size and Binning 15. The serial register continues clocking. 1 2 3 SW Output Node
Pixel Size and Binning 16. 1 2 3 SW Output Node
Pixel Size and Binning 17. The SW potential is set slightly higher than the serial register electrodes. 1 2 3 SW Output Node
Pixel Size and Binning 18. 1 2 3 SW Output Node
Pixel Size and Binning 19. The charge from the second pixel is now transferred onto the SW. The binning is now complete and the combined charge packet can now be dumped onto the output node (by pulsing the voltage on SW low for a microsecond) for measurement. Horizontal binning can also be done directly onto the output node if a SW is not present but this can increase the read noise. 1 2 3 SW Output Node
Pixel Size and Binning 20. Finally the charge is dumped onto the output node for measurement 1 2 3 SW Output Node