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PSP_001764_1880 (Zunil Crater rim) stands out to me, since I used it early on when putting together our color processing pipeline. It looked absolutely grey, so I figured I had made a mistake. Then I saw that gorgeous swath of blue on the crater rim, where it looks like a small landslide has exposed fresher material, and I knew everything was starting to work properly.

But a short list of the must-see-RGB would have to include these:

• PSP_001784_2630
• PSP_001784_2030
• PSP_001756_1995
• PSP_001754_2020 and
• PSP_001752_1750.

There are two nice isolated gullies: PSP_001712_1405 & PSP_001714_2390.

PSP_001720_1730 is missing one-half of the RGB color, due I think to IR channels that weren’t received. A recent update to our color processing will allow to go ahead and automatically produce the RGB product in cases like this.

The transition between dunes and an extremely steep scarp in PSP_001728_1995 is quite striking (see below, zoomed out 4x).

How about the Boulder race in PSP_001730_1740?

PSP_001732_2595 shows an interesting type of patterned ground, where boulders have shifted into a regular series of repeating lines.

PSP_001782_1195 is giving me trouble, some browsers won’t display it here; it is a bin-4 37500-line image.

Our former algorithm for the NOMAP and Quicklook products said that the pixel values above the brightest 0.1% and below the darkest 0.1% would be mapped to the extreme values, with a linear fit in between. For a majority of images, this was a good choice that showed excellent contrast but prevented too much saturation.

However, 0.1% (a thousandth) of a two Gigapixel image is still two million pixels. So if there were a particularly bright spot, like a rocky outcrop amid a field of dunes, or a particularly dark spot, like a cavern opening in a plain of boulders, then all the saturation would occur in that one area, washing it out completely, and lowering contrast everywhere else in the image. So the algorithm needed to be more adaptable. After a good deal of experimentation, the algorithm we settled on looks at the brightest and darkest pixels in a thumbnail version of the image, and uses those values for the extremes, instead of the values at 0.1%. We shrink a copy of each color band to 1/11th the original scale. Pixel values in the original below the darkest in the thumbnail are mapped to pure black, while pixel values above the highest are mapped to pure white. The stretched bands are then merged to make the color image. Hence, a bright or dark spot smaller than 1/11th x 1/11th of the image size will no longer dominate the stretch.

What this ultimately means is, our RDR Extras now show more detail in areas that would be completely washed out by the old algorithm.

For example, in this ‘cave’ image, the left is from the original RGB.NOMAP.JP2, while the right is the same product using the new algorithm. As you can see, previously you could not tell if there was a floor to the hole or if it sloped away to greater depths.

The new algorithm is used strictly for the JP2’s; the browse and thumb are already scaled down enough that it would not make a substantial difference with them. The new algorithm went into effect today; coincidentally we just started orbit 8000. Images with the new stretch will likely appear in upcoming weekly releases and we plan to reprocess everything with this change (and improved calibration) during the summer.

Here is a more specific description of our old and new stretch algorithms.

Old Algorithm

Determine the min and max DN value corresponding to the following cumulative
percents into the histogram.

For the full RDRs, the stretch is linear and the output is 10-bit and
preserves the special pixel values: 0 = NULL, 1 = Low Representation Saturation, 2 = Low Instrument Saturation , 1022 = High Instrument Saturation, 1023 = High Representation Saturation.

For everything else, the stretch is linear, 8-bits per band and each band
is done independently. Special pixels are not preserved.

New Algorithm

The JPG products (browse and thumb) are be made with the original algorithm, with the following exception.

• The Color JPGs use the same stretch as the IRB JPGs. (Otherwise, the black area around the rotated image change the stretch).

The JP2 products are stretched as described above, with the following changes:

• The min and max for the stretch are determined not from a cumulative percentage
  but from the min and max DN taken by reducing the image or band by a factor of

  11 * ( binning / binning of red band )

  . The reduction averages pixels.

Notes

1. Due to PDS format restrictions, the 3 bands of the color RDR (IR-RED-BG) are not
   stretched independently.
2. The ISIS applications hirdrgen and isis2raw are used for stretching. The latter for
   RDR quicklooks and NOMAPs.

Click the link below to view a gallery of 50 HiRISE images in the 1300 range, drawn from our online PDS data node. The RGB browse is shown in the window, linked to the full JPEG 2000 using the IAS viewer. The RGB browse scale image is usually scaled down by a factor of 8–in both horizontal and vertical directions–from the JP2 product. So the browse image shows you around 1/64th of the color data: there are vast and beautiful scenes that can only be seen in full by zooming in with IAS. Nevertheless, if you have some time, this is a good way to explore a set of images and get an overall idea of what there is to see.

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Most images are several times taller than your computer screen, so make sure to scroll through each one. Let us know which images are you favorite via the comments form below.

Updated (2008-Apr-10)