Making Panoramas in the Rainforest (part two)

Hi Folks:

Making digital panoramas is essentially a two-part process. In part one of this post I covered a bit about digital panoramas in general and some considerations that become important when collecting the images to be used for the panorama. Part two is focused (pun intended) more toward what to do with the images once you have them on your computer.

NB: If you have a smart phone you can use the panorama mode on your phone to make a simple panorama. Some even allow you to create a panoramic image from a video. Depending on your phone and your expectations, that may be sufficient for your needs. For me, it’s mostly not, because one of the benefits I find in making a digital panorama is the increase in resolution I obtain from joining together several images into one. The downside to that is that file sizes can get quite large, so when rendering the final image file it’s best to balance what you want against the capabilities of your computer. Sometimes I try to make smoke come out of mine… 🙂

This post is (typically) very long, and so we’ve broken it up into segments for you. Clicking on the subtitles will bring you to the relevant section:

How Panorama Software Works
Projections
Panorama Software Options
Making Panoramas
Stitching Errors
Exposure and Image Noise
Parallax
White Balance
Chromatic Aberration, Fringing Colour Artifacts
Image Cropping
Keystoning
Final Thoughts

Continue Reading →

Panoramic Photography and Stitching “Errors”

Hi Folks:

In a previous post I rambled on a bit about panoramic photography – basically a system where one combines several images into one using software designed for that purpose. One can also take several images of the same scene at different exposures and combine them into one HDR image using the same software. Mostly I use Autopano Pro for stitching, although I’ve also used Hugin, and since I work extensively in Lightroom I’ve been playing a bit with Photoshop CS5‘s HDR Pro and panorama tools as well. To create a stitched image the software looks for the same points in two or more images and assigns them as ‘control points’. The combined image is then mapped around those control points. Usually this works very well, but in my previous post I talked a bit about parallax errors and things like that, and sometimes these images don’t get mapped together perfectly. This can create situations like this: Continue Reading →