New address

Most posts from this blog have been copied to a new server, run by myself. The idea is to make it easy to invite contributions from outside the university, and to have more flexibility in the administration of the site. If you are subscribed to e-mail updates to this site, you will need to subscribe again at the new server. In the new server you will no longer receive repeated messages each time I fix a typing mistake! (At last!)

The new address is:

See you at our new “home”! There are already some new posts over there.

Digital imaging: stretching the limits


In coming months I will write a series of posts with brief presentations of imaging methods that are nowadays accessible and very useful for research. In many cases they are of help also for other types of documentary photography and for artistic photography. Some of these methods have been around for some time, but their use has become easier as cameras and computers, and their software have evolved. The posts will be brief but will contain links and references to help those who want to explore them in more depth. I will show examples of both software and equipment. In most cases I will include example pictures produced by myself.

I will in the first few posts describe methods that involve merging of separate shots. These methods can be used with any digital camera with manual controls and/or specific automated functions. Some modern cameras can even do the image merging almost in real time. Most of the methods can be also used with digital images obtained with a microscope.

Methods based on image merging

  • HDR: high dynamic range, the merging of images obtained using different exposure values into a single image representing a wider range of luminosities within the curve extending from black to white.
  • Focus stacking: the merging of images obtained with the focus point slightly shifted into a single image with more depth of field. In other words with a wider distance between the nearest and farthest point in sharp focus.
  • Panorama: merging of partially overlapping images into an image with more pixels and a larger subject area.
  • Enhanced resolution: merging of images displaced by less than the size of a single pixel to obtain images at a higher resolution than the sensor’s pixel resolution.
  • Object removal: removal of moving objects by merging images obtained when the moving object(s) covered different areas of a background of interest.

Methods requiring special cameras or modified normal cameras will  be described next.

Methods extending the wavelength range or wavelength resolution

  • Thermal imaging: the pixel values describe temperatures, which are derived from emitted infra-red sensed through and especial detector and lens.
  • Digital photographs at wavelengths outside those visible to us: imaging based on ultraviolet or infrared radiation.
  • Hyperspectral imaging: normal digital images have three components: red, green and blue (RGB). In spectral images each pixel is represented by spectral data of much higher wavelength resolution. Hyperspectral images are spectral images in which the spectral range extends outside the range of wavelengths visible to humans.

Methods involving extending or contracting time

  • Time lapse: merging of static images into a video with accelerated time
  • High speed photography: imaging of objects moving at very high speed for reproduction at a slower frame rate.

Limits to image manipulation

  • How much can one edit a documentary image without misrepresenting the object being documented? This is a controversial question both for images used in scientific and news reporting.
  • Image edition and reproducibility. Destructive and non-destructive methods of image manipulation. Loss-less and lossy image compression.

The reason behind this series of posts is that these methods are in use, or will be soon in use in my research group. I would have anyway to write this texts for those working with me, so why not do this is in open?

New name, new aim, new target audience

When I started this blog I had hoped it to become a communication channel for our division’s teachers and our students. In about two years, I have been almost the only one writing posts. Very few posts have been related to activities or events in our division. Because of this, I am changing the blog’s name to one that reflects better its real contents. I will from now on advertize it more widely and include even more varied content.


About planning (or not) your future

I have been quiet for some time, but I will try to post a bit more frequently in the future. This time my post does not have any direct link to plant biology. After watching this video a couple of days ago I was nicely surprised to learn how lucky I have been. Although I am a rather extreme case of a person having many different interests, I have very rarely felt the pressure described by the speaker. In fact many times I have felt encouraged. This may have to do with a different cultural attitude in Argentina, and in addition, because I have almost always connected all those different interests. So, what are those interests? I have training as a crop breeder, but I did find very interesting plant eco-physiology, genetics, micro-meteorology, statistics, systems analysis, computer programming, electronics, photography, and graphics/book design. This seems too much! Doesn’t it? Surprisingly I am using all those skills and interests in my current research and teaching. I did my first experiment with plants, as an undergrad, around 1978 and quite soon after that I designed and built my first measuring instrument, an auxanometer (an electronic instrument to measure plant growth rate with a very good time resolution, of minutes, if not seconds). For this I used what I had learnt of electronics, mostly as a  hobby, and from a friend who studied telecommunications at a technical high school. Then we got the first computer in the lab, an Apple II. Money was scarce, and we had a commercial statistical software that was so awkward to use that I do not think a young person nowadays could imagine that anybody would ever write a program, and be able to charge money for it, where you had to type-in the numbers to analyze one by one, and had no provision for editing any data value after you had entered it. In other words, if you made a mistake, you had type-in again your whole data set! I was not happy with that, so I just wrote a programme myself for ANOVA and ANCOVA. Combining what I had learnt of statistics in regular university courses with what I had learnt about programming mostly by myself, again as a hobby.

I hope none of those of you who do have many different interests, is feeling the pressure described by the speaker. If you do, however, stop worrying, and find ways of combining those interests so that you can either use them together, or alternate among them.



The researchers behind ‘the biggest biotech discovery of the century’ found it by accident in DNA Research

[Business Insider] The discovery of the CRISPR genome-editing technology shows why basic research is so important.

Source: The researchers behind ‘the biggest biotech discovery of the century’ found it by accident in DNA Research

I am posting this as an example that when doing research one has to broadly think how what one is working on may have useful implications for different problems than those we are aiming to study.

The other point, is that basic research, even if it does not have a known or expected application can have a huge contribution to solving practical problems.

Some additions from yesterday’s session

1) Microsoft is using R internally, and what is more, they are going all out for R: it has already announced that MS SQL database’s next version will have R built in. Test release is scheduled for September. It has acquired Revolution Analytics. Microsoft is also funding R development through the R Consortium  announced 4 days ago, under the umbrella of the Linux Foundation.

2) There are rumors that some future version of Excel will have R built in!

3) R is being now accepted in the financial and commercial world and is quickly replacing SAS.

4) Just a single company called Teradata has more than 400 open vacancies for employees with R experience.

5) Hewllet Packard is releasing its own version of distributed R as open-source software.

6) Next UseR! meeting will be at Standford University and the organizing committee includes members both from Microsoft and Google.

I think it is time for our department and the whole university to stop teaching SPSS to our undergrads and switch to R as our main statistical software.