MSL Images & Cameras, technical discussions of images, image processing and cameras Options

[CosmicRocker]

I'm still trying to figure out a number of things about the new images we are trying to work with. Assuming others are likewise trying to learn, I thought I would open this thread to create a place for such discussions.

I'd like to start out with a comment about raw image contrast. There have been several postings in the main threads about whether or not the MSL raw images have been stretched like those from the MER missions. I am certainly no expert on this, but it looks to me as if the MSL images have not been stretched at all. I haven't tried to analyze all of the image types, but the hazcams and navcams have pixel brightness histograms that are very different from their MER counterparts.

This attached image compares MER and MSL navcams along with their luminosity histograms.


The MSL images clearly are not using the entire, available range of brightness values, whereas the MER raws do. For this reason, the MSL raw images can usually be nicely enhanced by simply stretching the distribution of brightness across the full 256 value range.

[EdTruthan]

Sorry for the long post but if this works as a fairly accurate white balancing trick I wanted to get everybody's take on it and share the technique...

The white balance issue (thanks for bringing it to the forefront mcaplinger) certainly is a pesky one for imagery geeks like myself. Where there is a calibration target in the image its a pretty simple task to equalize RGB values based on a gray target. Mcapliger's general adjustment values are certainly a move in the right direction. But with so many differing landscapes and lighting values based on time of day, sun angle, and atmosphic dust content, and absolutely nothing to accurately base mean gray values on, I've been struggling with how to find a method of determining just how one would go about getting an accurate white balance with any given image. This morning I stumbled across a technique that after a some extensive tests seems to show promise...

I was remembering how if one takes a color image (any image that is, Earth based or not), and copies it into another layer, inverts the color, and reduces the opacity of that inverted upper layer to 50%, the transparent inverted colors cancel out the colors of the original image below, leaving a blank neutral grayscale image. Using this concept and and a few tools in Photoshop (requires any CS version) I created custom photo filters (that vary slightly on a per image basis) that appear to white balance the Martian atmospheric tinge on calibration targets near perfectly, and so by extension one could argue the landscape as well.

Here's the technique I used for the following examples (I suppose one could loosely refer to it as "IBF" or Invert > Blur > Filter):

1. Open an MSL image in Photoshop.
2. Duplicate the "Background" layer. You now have a "Background copy" layer above the original.
3. With the "Background copy" layer selected, choose "Image > Adjustments > Invert", then "Filter > Blur > Average". You should now have a bluish single colored blank layer.
4. Use the eye dropper tool to select this color as your foreground color on the tools palette. Now turn this layer off so you can see the original image.
5. Now select your MSL image layer again ("Background") and choose "Image > Adjustments > Photo Filter..."
6. In the dialog that opens choose the "Color" radio button and click on the default color swatch and assign it with the bluish foreground color you saved on the tools palette.
7. Move the slider to 95%. (determined because at 95% the calibration target gray RGB values are closest).

Now if the image you're using is a landscape shot you're going to notice the color has washed out quite a bit. This is the filter at work. Just do the following.

8. Choose "Image > Adjustments > Hue/Saturation..." and increase the Saturation Slider to about 55-60.

This last adjustment is about where most of the tests I ran on landscapes seemed to restore the color to about the intensity of the original, though admittedly it's arbitrary. In fact, the calibration target samples below only seemed to require a 25-30 increase in saturation, as any higher seemed to over saturate them. I take this to perhaps be and indication that the farther away the target, the more saturation "recovery" must be applied (due to the extra desaturation effect of the atmosphere?).

Using this technique on an image by image basis (i.e. the precise color of the filter varying as per the inverted, blurred averaged color of the original) I was able to achieve the following results. As the technique seemed to almost perfectly balance the white, gray, and black levels of the calibration targets, could we then assume that the landscape color values must then be similarly accurate? Hmmmm.