Meteors

Perseid meteor shower captured with the Canon's A2200 camera using CHDK to override the exposure to 20 seconds and a script to continuously take pictures till the battery runs out.

But even with ISO set to 1600, the majority of the meteors were to short lived and not bright enough to be captured.

Science & Engineering

Curiosity successfully landed on Mars!

To celebrate here's a 10x enlarged photo of the descent using b-splines.

B-splines "HD"

Full resolution panoramas with nearest pixel values and sub pixel values.

B-splines

What an interesting thing this is.

With it you can resize this:

To this:

Without looking like this:

While used to describe continuous surfaces in 3D models, their ability to produce a value at sub pixel resolutions con be abused here to unfold the 360° panorama more smoothly.

Panorama when unfolding with the nearest pixel to the calculated value:

Panorama when unfolding with the sub pixel value:

The down side is that using brute force to calculate every pixel amounts to couple of hours per full resolution image.

Next step, use science & math to speed things up!

And to finally fix the aspect ration (now that the images are smooth).

Data Set Test

Time to collect some sample data!

The plan was, take a stereo picture with the lenses apart from 155 mm to 955 mm with 50 mm intervals. After that, process them and see how the space between lenses correlates between produces images. That was the plan.

What I did discover is that there is a small design flaw in the set up. The mount that holds the camera is prone to swivel when moving the camera left or right on the tubes. Which means that if not really careful, the cameras weren't always pointing perpendicular to their location. Which means the depth perception doesn't correlate with the camera position.

But the pictures are awesome!

It's all About the Ratio

That's better!

Sorting out the aspect ration issue (should the width and height be determined by the difference of surfaces from inner our outer circle or be set by the radius & circumference), still needs some work.

But the next big challenge is to antialise the image.

1 != 1

And suddenly the problem comes in to focus!

It was not, as previously thought, a problem with the lens distortion or pixel shape. Or any other mythical unexplained reason. No, just a simple mix up with with the normalisation of the vectors.

If the image is not equal in height and width, then 1 X != 1 Y.