De Rotation of Images in Planetary Astrophotography

Basic Concepts

Fernando Rodriguez,SFAAA

Contrary to popular belief, high quality planetary imaging is no easy task although planetary imaging is by far the easiest way to get started into Astrophotography. Planetary imaging requires less hardware and most of the software required is available free on the web. The basic cameras are far less expensive than the low end counterparts for Deep Sky Imaging available in the market. Although all this is true, the more advanced the imager becomes in this work, the more hardware and software is required to obtain high quality images. It is not the purpose of this article to discuss in detail the basics of planetary imaging but to describe in very basic terms how high quality planetary images can be obtained by focusing in one of the most difficult tasks which is capturing enough data in order to reduce the signal to noise ratio of an image.

Principles of Planetary Image Capture The first thing we need to have clear is how we capture images in planetary imaging. Lets take a look first at Deep Sky Imaging. Most people are familiar with the fact that photos taken in dark places require long exposure times. The same is true for deep sky imaging. People who take those images expose their targets using several filters, sometimes for hours. This requires special software, special cameras and also a guiding system to keep the track of the mount in perfect sync with the apparent movement of the stars above. This is in order to eliminate those oval shaped stars (or actual trails) when the image is left to the tracking of the mount alone. This is achieved by using a second camera centered in a star and via software, the program “tells” the mount to make small corrections so that you can obtain perfectly round stars. It is the same as if you take an image for a few seconds of a person walking at night with a flashlight. You will end up with an image with a long light trail in weird shapes and probably an almost unrecognizable person unless you are able to perfectly follow the movement of the flashlight (which is quite hard to do). An example of such a technique can be shown in image below. It is an image of the Great Orion Nebula. It is a 20 hour exposure of different images captured using several different filters. These objects are rather large and dim compared to planetary targets so long exposures are required and several different filters are needed to obtain not only color but to extract features such as the interstellar dust present in any of these objects.

Jupiter Oct 28, 2013, Celestron HD 8” Fernando Rodriguez, Weston,FL

Great Orion Nebula using Luminance, Red, Green, Blue, Hydrogen Alpha Albert Barr, SFAAA, Phoenix, AZ

High quality planetary imaging is very different. Solar system objects are mostly captured using streams of images recorded as videos, usually as an AVI format file. Cameras run at very high rates often at 50fps to over 100fps. There is no long exposure times. Each of those frames can run at exposures of 10ms to 20 ms depending on the scope camera and general setup used. So what goes behind planetary imaging is to capture this AVI video and then somehow separate the video into individual frames (like old cartoons) and obtain hundreds to thousands of frames of the object being imaged. The idea is to capture images so that we can increase what is called the Signal to Noise ratio or S/N. A little bit of explaining here. Each digital frame or image is basically a digital file. It contains data of two kinds. The Image itself and Noise. The noise is caused by many reasons, mainly due to thermal noise and also readout noise (although there are other sources of noise associated with the whole process which is not really our interest here). Thermal noise is noise associated with the temperature of the sensor. If the sensor increases temperature, each file it generates will have a component of noise caused by those excited electrons due to thermal energy. A sensor can not identify if the electron comes from a planet or a nebula or was generated by the system itself. For this reason CCD cameras for DSO imaging are usually cooled to reduce the noise generated by a hot CCD sensor. Since they have long time exposures they need to reduce this thermal noise as much as possible. Although planetary cameras are not cooled, they also get hot but since captures are short fast running frames, the amount of noise can be reduced by simply capturing as many frames as we can. The math which isn’t simple, says that as I increase the number of frames I capture and add them, the amount of data with respect to the noise, increases. So the division of S/N if S becomes large (trust me on this) gives as a result that the amount of noise (compared to the image data) gets reduced significantly. That is where the secret of high quality planetary images comes. Capture as many GOOD frames as possible.

Planets Rotate Yes I know you are aware (I hope) that planets rotate. Planets in our solar system rotate at several different rates. The reason? Well all formed from the same cloud but formed at different distances and under particular circumstances. That made them what we see today. Venus for example rotates so slow that its year is actually shorter than its day. Mars is almost identical to Earth in many aspects. It is tilted almost the same as Earth is and its day is almost the same as Earth around 24 hours. On the other side, Jupiter and Saturn are planets whose rotation is very fast. It takes around 10 hours to spend a day in one of those gas giants. One of the most famous features in Jupiter is the GRS (Great Red Spot). It is a fast rotating mass of gas on what we would consider the “surface” of Jupiter. It is so large that we could fit three or four Earths inside this oval shaped feature. In small scopes you can see it from Earth. The GRS can transit from left to right in your telescope (or the other way around if you don't have a corrected view) in just about about 5 hours. You can literally see it move during an evening observation. So here is where the need to gather lots of good frames for an image and the rotation of the planet come into conflict. The more frames I take the more time I give the planet to rotate so it may come to a point where a feature like the GRS is in one place where I started shooting and in a very different place 10 minutes later. There are two ways out of it. One is to use a color camera or OSC (One Shot Camera). This is fine especially if you consider one of the high end cameras available today. It can be the famous Imaging Source cameras or the newcomer in the market place ZWO. You can shoot one single stream of video at rates anywhere from 50 to 100 fps during about 120 seconds and you can easily obtain in excess of 3000 frames. More than enough to process. But unfortunately, color cameras do not have the Quantum Efficiency Levels (ability of pixels to gather photons) of MonoChrome cameras and also do not have the same level of resolution due to the use of a Bayer Matrix to obtain color. (click here Bayer Matrix). Using a Monochrome sensor external filters will provide the three basic colors using all of the pixels of the sensor (shown in grey) while the Bayer Matrix will share pixels among the colors to obtain a single image. So in the figure below we have a sensor with 64 pixels. The Bayer Matrix will use 25% for Red, 25% for Blue and 50% for Green to compose a color image. Using external filters in a filter wheel at the telescope and a monochrome camera we will use all 64 pixels for each of the colors in three separate videos and then combine all three to a single color image.

Resulting pattern using a Bayer Matrix to obtain color on a monochrome sensor. You can observe that the matrix will share the pixels of the sensor among the three colors to provide a

single image. Wikipedia

So the most important concept here, is that when doing high resolution planetary imaging, the use of a monochrome camera is preferable and also that when these cameras are used the fact of taking three or four separate videos to obtain an RGB or LRGB image will take more time. Imagine using 5000 frames for each set and being able to image Jupiter at 50fps, it will take around 6 minutes and 40 seconds to capture that information. That alone will make each of the frames L,R,G and B themselves be shifted as the planets rotate. How do we fix this? Well here is where a very interesting piece of free software comes into the game. WINJUPOS

Luminance Red Green Blue

Above you can see the four files that compose the image below and were captured in the order shown. Each frame corresponds to one filter. They are all shifted in time due to the movement of Jupiter and although not immediately evident, if you compare Luminance with Blue you might be able to see that the GRS has moved towards the center in the last frame. When assembling a color image, this displacement will cause the image to look blurred since features will not match its position in each of these frames unless you de rotate them in a program such as Winjupos.

Jupiter composition of LRGB frames applying de rotation algorithm from Winjupos, Fernando Rodriguez

In the next part (Part II) we will use all the current concepts we have seen here and apply them in WinJupos in order to de rotate images of an LRGB capture and integrate them into a final color image. We will try to do this step by step.

Introduction to Winjupos In the words of the Author Grischa Hahn: WinJUPOS is the result of long-time work of amateur astronomers to support observation and analysis of phenomena on planets of our solar system. The core of the software is a database of positions of objects in the atmosphere, or on the surface, of the planets and the Sun. It began with an electronic data collection, as part of the International Jupiter Voyager Telescope Observations Programme (IJVTOP), made by Holger Haug and Christian Kowalec on VAX machines in the 70's. In 1989, Hans-Jörg Mettig developed the Central Meridian Transits Project (ZMPP, version 1) for Jupiter, which made possible a first data management and analysis on PC's under the operation system DOS. In 1992 the author, Grischa Hahn, resumed development of this program, and later produced the DOS softwares PC-MAPOS (Mars), PC-JUPOS (Jupiter, versions 2 to 6) and PC-SAPOS (S“aturn), as well as numerous utilities. Due to the rapid technical progress, software porting to WINDOWS became more and more urgent, and finally started in 2002. WinJUPOS (to version 7) comprises all previous developments”.(1) So basically what Winjupos can do is a lot of things. It can help in planning an observation, predict when a specific feature will appear, you can measure in miles or kilometers a specific feature on an image and you can also report your observations to a central database, record Central Meridian Transits etc. For more information on what Winjupos can do you can visit: http://www.grischa-hahn.homepage.t-online.de But for the planetary imager, the most interesting feature of Winjupos could be De rotation of images. There are three basic routines in Winjupos. One is De rotation of RGB images, another is de rotation of AVI videos and De rotation of images. The first one is the most important and the one we will target in this article. Basically capturing a set of LRGB videos and transforming them into three or four separate individual images (R,G,B) or (L,R,G,B). The capture process will be topic of another article. Now we are taking this step from the captured videos that are aligned and stacked into programs such as Autostakkert or Registax and converted to a stacked and aligned single image for each of the L,R,G,B channels. So the first step is to open a file in your computer and place those 4 TIFF images in there so we can start the process with Winjupos. At this point we still have not done any post processing, we have the raw images coming from the camera and stacked and aligned with only wavelets done in Registax for sharpening. We have not done any light levels or noise reductions or Saturation and Hue changes, extra sharpening or filters. That all will be done once we have assembled the final color image generated by Winjupos. Measurement Measurement is the first part of the process. We feed Winjupos with each of the images. One thing that is important, when capturing and stacking images we need to try to have software that will place Universal Time information on the file names so that Winjupos can know when the images were captured. Each channel will have different times so the software may bring all images to the same point in time. This is not mandatory but makes things easier than you wondering the UT for each file when adding it to Winjupos. As shown in figure 1 below, the first step is to open Winjupos and select the celestial body you are going to work with. In this case Jupiter. Once you have selected jupiter you go to Recording and click on Image Measurement. (Figure 2)

Figure 1

In this part on the top we click on Open Image and load the image we want to measure. In this case I always start with the Luminance channel. Note that below “Open Image” there is a space for Date and also Longitude and Latitude. Date and Time are loaded directly from the file if the UT stamp has been set in the capture software and kept during Autostakkert and Registax alignment and stacking. The Long and Lat are settings that can be saved if you are capturing images from the same location if not you need to modify those to match the capture site. Further down there is a space for Image info. I usually add LUM, RED, GREEN or BLUE in this space but that is something you can fill with whatever information you feel important of the image. Figure 3 shows the screen wham the image is loaded.

Figure 2

Figure 3

Note that when the image is loaded, a circle or outline of the planet with a N and P will appear. Now you must move to the Adjust tab right above the Open Image button (Figure 4). The outline will not necessarily match the image and you will need to adjust it for each object both in size and position. In this case it has already been adjusted to match the image perfectly. On the Keyboard you will use Letters N and P to rotate the outline (clockwise or counterclockwise) as well as keys “Page Up” and “Page Down” to increase or reduce its size. The arrow keys will move the outline up, down,left or right. You can also see a small circle on figure 3, to the left of the image, signaling where one of Jupiter’s moons should be and should match your image. Make sure to adjust the outline as tight to the edge of the planet as you can. These controls will be only available when you are at the ADJ tab not on the image tab.

On the ADJ tab at the top you will find a drop down window where it says “Channel (F9), to select a type of image or color. In this case since you are working on LRGB files then you choose which color channel you are processing. For the current image on Figure 4 since we are measuring channel Lum or L we select Grey. Once you have moved to the Adjust tab and filled out the type of image you are measuring, you must return to the previous tab and save the image. Make sure you save everything in the same folder. Do the same process with all your L,R,G and B images. You will end up with four files with a format type .ims in your folder one for each of the channels. Once you have done that you are ready to merge and execute de rotation of RGB images.

Figure 4

Figure 5

We have reached the final step of our process to de rotate and obtain a full color LRGB or RGB image. Go now to the top and click on Tools. The screen shown in figure 5 will appear. You have four areas where you can load your .ims files you worked before. Just click on the blue square next to the red X to load each image. Red, Green and Blue. Further down you will find the Luminance. Click on the Destin Directory and select the folder where you want to store your resulting image.. Make sure that you have selected Image type to TIFF and that you choose if you like North Up or South Up (its up to you). I never select stretch luminance to maximum but that is also a personal preference. Click on Compile Image and the process will take a few seconds. The color image will appear in the screen as show in figure 6

De Rotation and Composition of a Color Image. This whole process will now end with obtaining a single color image form one run of L,R,G,B captures in AVI format (or SER). I have to make a note here. We are only using the De rotate RGB portion of Winjupos. There are two other routines where you can de rotate an AVI file (movie) and also you can create several runs of RGB, RGB1 RGB2 RGB3 etc and then recombine all those in which case you will use the De rotation of Images. Here we are only doing de rotation of ONE set of LRGB images.

Figure 6

The image is finalized. Now you have a single color image that you can send to Photoshop or whatever image post processing software you want to use. So there it is, Winjupos is a very powerful tool for any planetary imager or for anyone with an interest to measure, predict or share information of any planet. A final note. Winjupos works for several bodies in the Solar System not only for Jupiter. You can use it for Mars, Saturn and technically for all the planets, the Sun and the Moon.