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Jeremy's House - jagged Yuris Hills low

Date: August 14, 2013
Screenshot #431: After 2 days of work, processing 256 total objects (1/4 of which in just the 4 closest layers alone), I finished the Yuris Hills in Jeremy's House. Although the jaggedness is visible, especially with the closest layers, the Yuris Hills are not mountains and are very smooth. The Yuris Hills are just large hills. This makes the conical lighting the dominant difference.

Jeremy's House - jagged Yuris Hills high

Date: August 14, 2013
Screenshot #432: From a much higher vantage point, the farthest of the Yuris Hills are visible. Jaggedness, almost too slight to notice, has practically no effect so it's almost pure conical lighting. Just that change alone has a significant quality improvement. This also best illustrates how much of an improvement just the conical lighting alone has.

Carnivalesta - jagged mountains low

Date: August 15, 2013
Screenshot #433: After another day of work, processing 90 more total objects (6 of which already done due to reusing a layer in the Sentus Mountains), I finished Carnivalesta's Sentus Mountains. Are your photon detectors (aka eyes) in good condition? Because it's so dark, due to being night, it's very hard to see the jaggedness. If you look closely, however, best viewed on a dark background in a darkened room, you can see the jaggedness. This scene shows the bulk of the closer objects where the jaggedness is the easiest to see.

Carnivalesta - jagged mountains high

Date: August 15, 2013
Screenshot #434: From above the clouds, it's easier to see the farthest mountains with the rather bright ice caps. The jaggedness is still very difficult to see though, even with optimal viewing conditions, made even harder due to the fog. The jaggedness is visible if you look closely enough. Are your photon detectors (aka eyes) working very good?

Nodera Ice Shelf - jagged mountains

Date: August 16, 2013
Screenshot #435: Another 80 more objects and the Sentus Mountains in Nodera Ice Shelf are done. Due to the clouds almost completely obscuring the mountains, I'm only using a single screenshot from the best vantage point I can find and think of. Due to being purely covered in snow and ice from being so far north, the jaggedness is very easy to see. Like with Carnivalesta, the foothills are not as jagged as the big ones as they've undergone more weathering and erosion than the taller cousins. Of course, don't forget that distance also plays a role too.

Nodera Highlands - jagged mountains

Date: August 16, 2013
Screenshot #436: Unlike the previous cases, the 72 objects here were done differently. Because this section of the Sentus Mountains only barely pokes through the clouds, I didn't have to extend any of them so it was nothing more than saving the shape images, running them through my program, importing the output from the program, and adjusting it as usual. It was much faster to do. Because the objects needing the jaggedness are only visible above the clouds, there's only the need for one screenshot as much of what's in focus can be seen. However, because the mountains repeat every 64 Kbl, it's never possible to see all of them at once, even just 20% of them. It is possible, however, to see every layer and that's what I've done.

I actually made a very slight modification as well. Instead of being at 384 SU and stepping by 128 SU per layer, I have the spacing varying slightly. The closest, shortest layer is now at 448 SU. Instead of stepping by 128 SU, the shorter layers are closer together. It just makes more sense. The image pixel data isn't being changed aside from the jaggedness being applied. The shape isn't being changed though - I have no need to do so.

Mount Sentusia - jagged mountains

Date: August 17, 2013
Screenshot #437: The 40 objects for Mount Sentusia are exactly identical to those in the Sentus Mountains. The only difference is that the tree and snow lines are adjusted from being at a higher elevation but also a higher latitude. The shape hasn't changed (aside from the standardization of the layer at 1280 SU as I had 5 objects instead of 6). Since the image changed from the shifting tree and snow lines, the shape hasn't changed, and to enhance variety some, I decided to simply rerandomize the jaggedness for Mount Sentusia's mountains. This screenshot shows the results.

Keveran Desert - jagged mountains low

Date: August 18, 2013
Screenshot #438: While processing the Keveran Mountains in the Keveran Desert, I recorded a video detailing how I apply the jaggedness, a rather long video nearly 2 hours long. There were 120 total objects in this set and processing them was done in the usual way. The results are shown in this screenshot quite well, for the closer ones that is.

Keveran Desert - jagged mountains high

Date: August 18, 2013
Screenshot #439: From a much higher position, it's much easier to see the farther parts of the Keveran Mountains, along with... Lake Keveran? Although I haven't officially decided yet, I'm considering making that far area Lake Keveran instead of the ocean.

Sky darkening - updated dusk sky

Date: September 10, 2013
Screenshot #440: Knowing that the dusk/dawn sky had too high of a saturation, I wanted to change it. With it now known that CreateDIBitmap can allocate memory like malloc, I no longer have the rather complex system I had for memory management. This means that the array sizes can vary. The sky darkening effect had plenty of optimization potential to it for memory and it turns out that I'm saving about 1 1/2 MB of memory after making the enhancements. That doesn't seem like much, but with a 96 MB target, that's quite significant.

One of the intended changes thought of nearly a year ago, was that I wanted to enhance the dusk/dawn sky. The saturation was originally around 70%, much too high. From seeing real sunsets, I now know that it's not 70%, but more around 50%. So, after spending a few hours figuring out how my "overly complicated" algorithm is, I reworked the dusk/dawn sky so that it was lower in saturation. I also wanted to brighten the dusk sky, especially near the horizon. The end results are shown in this screenshot.