From wikipedia: In photography and optics, vignetting is a reduction of an image’s brightness or saturation toward the periphery compared to the image center.
When presenting a collection of images as a mosaic, the vignetting in the imagery can cause visual discontinuities at the image borders. Here I present a simple strategy to model and correct the vignette in a collection of images.
Step 1: Compute the pixel-wise average for a set of images
I start by creating 2d numpy array of float32 type with the same dimension as our camera. Each [u, v] position in the numpy array is … Read the rest... >>
Recently I flew a DJI Phantom 4 Pro v2 head to head with an in-house (U of MN AEM UAS Lab) developed fixed wing UAS. This comparison isn’t entirely apples to apples, but maybe someone will find it useful.
DJI is the king of the hill for small UAS aerial surveys. Once you figure out the apps and a few basic things, operating one of these is pretty much click and fly and makes aerial survey work about as easy as it can be. Some quick details of our system:
Camera horizontal field of view: about 67 degrees.
For this episode I present a plot of optimized camera locations. I have a set of 840 images. Each image is taken from a specific location and orientation in space. Let us call that a camera pose. I can also find features in the images and match them up between pairs of images. The presumption is that all the features and all the poses together create a giant puzzle with only one correct solution. When all the features are moved to their correct 3d location, when all the cameras are in their correct … Read the rest... >>
Zombies are pretty cool. This post describes something a little less cool, but uses zombies to explain the concept (in a shallow, transparent attempt to capture your attention!)
Zombie Door Method
Imagine we want to generate a uniformly distributed random sampling in some complex space that our random number generator does not directly support.
Let me start with an simple example. Imagine we have a random number generator that produces a random integer between 1 and 100. However, we actually want to generate random numbers between 41 and 50. (I know there are better ways to do this, but … Read the rest... >>
This is a short tutorial on an automated method to extract and geotag movie frames. One specific use case is that you have just flown a survey with your quad copter using a 2-axis gimbal pointing straight down, and a gopro action cam in movie mode. Now you’d like to create a stitched map from your data using tools like pix4d or agisoft.
The most interesting part of this article is the method I have developed to correlate the frame timing of a movie with the aircraft’s flight data log. This correlation process yields a result such that for any … Read the rest... >>
During the summer of 2014 I began investigating image stitching techniques and technologies for a NOAA sponsored UAS marine survey project. In the summer of 2015 I was hired by the University of Minnesota Department of Aerospace Engineering and Mechanics to work on a Precision Agriculture project that also involves UAS’s and aerial image stitching.
Over the past few months I have developed a functional open-source image stitching pipeline written in python and opencv. It is my intention with this series of blog postings to introduce this work and further explain our approach to aerial image processing and stitching.… Read the rest... >>
This is pretty cool just by itself. The above images are downsampled, but at full resolution you can pick out some pretty nice details. (Click on the following image to see the full/raw pixel resolution of the area.)
The next logical step of course is to stitch all these individual images together into a larger map. The questions are: What software is available to do image stitching? How well does it work? Are there free options? Do I need to explore developing my own software tool set?
I recently went through the process of trying to move my entire 1.5 Tb BackupPC tree to a new drive. Here are some thoughts and comments from that experience.
I spent 40 days (literally) attempting to get various combinations of rsync, tar, cp, etc. to clone the contents of the drives to a new larger drive. However, the bazillion of small little files hard-linked to a pool of randomly named actual files made this practically impossible to do in a finite amount of time.
In the end I used the unix utility ‘dd’ for the fastest possible copying.
The gumstix.org wiki has a page on how to configure your gumstix to auto-login on boot. This can be very nice for “production” systems where the intention is to power on and run some specific firmware/code every time.
However, with the new Yocto/Poky images based on the 3.5 kernel, things have changed and the old instructions no longer work. Here is a quick recipe to get autologin running again on the newer systems. First of all credit to http://fedoraproject.org/wiki/Systemd for their section on setting up autologin on a virtual terminal with the new systemd architecture.
Follow the instructions at the above link. However, there are several places where the standard openembedded build breaks. Here are the Fedora 14 specific problems I encountered with specific fixes and work arounds. This is a moving target so if you run into new issues, feel free to let me know and I’ll update this page. In all these cases I found solutions by googling, so if you have encountered … Read the rest... >>