{"id":10891,"date":"2025-03-20T12:24:06","date_gmt":"2025-03-20T16:24:06","guid":{"rendered":"https:\/\/starlightcascade.ca\/blog\/?p=10891"},"modified":"2025-03-20T15:13:48","modified_gmt":"2025-03-20T19:13:48","slug":"firecapture-roi-and-cutouts","status":"publish","type":"post","link":"https:\/\/starlightcascade.ca\/blog\/2025\/03\/firecapture-roi-and-cutouts\/","title":{"rendered":"Firecapture ROI and cutouts"},"content":{"rendered":"

Lucky imaging, Firecapture, ROI and cutouts<\/p>\n

Planetary Imaging took a Quantum Leap with the advent of Lucky Imaging and digital cameras.
\nLucky imaging is the process of taking thousands of very short (millisecond) exposures, analyzing them, taking the best x% and stacking them to get a great signal to noise ration and images that surpass film based, ground based images from only a decade or two ago.<\/p>\n

The shorter the exposure, the better chance of capturing a still image freer of distortion caused by atmospheric bad seeing. So the higher frames per second is the measure to work for.<\/p>\n

I recently submitted an image of Mars to the BAA along with some information like… 2ms exposure and I was getting 100 frames per second (fps). 1000\/2=500 fps theoretical and I was getting only 20% of that. The recommendation to me was to improve! Get a faster FPS! And use the ROI (Region Of Interest) and Cutout boxes in firecapture.<\/p>\n

With the full resolution of the ZWO ASI585MC camera (3840×2160 pixels) and a 3.5ms exposure, I got 47 fps, or about 16% efficiency. The ROI reduces, at the camera, the amount of data coming down the usb 3.0 pipeline and results in increased frame rates.<\/p>\n

I had been using a ROI of 1200×1200. That increased the fps to 83 from 47 (full resolution) and 29% efficiency. My best test result was using an ROI of 400×400 that achieved 220 fps or 77% efficiency.<\/p>\n

There are issues with tracking and keeping the image in the Field of View (FOV), especially in bad seeing, where the image jumps up down left right and in and out) when the ROI is small.. that is why I had a bigger 1200×1200 FOV to start with.<\/p>\n

The next feature I started using recently was the cutout box. This centres the image in the FOV and does it faster than the autoalign feature in Firecapture. It also reduces the amount of data saved to file.
\nInitially I started using a cutout box of 600×600 and am now testing it down to 400×400.<\/p>\n

One other new feature that I was unaware of was the ability to have the ROI centre itself. In the past, I would set the ROI and in the 120 seconds of imaging run, the target would stay in the FOV, but maybe not the next or the next runs, without manually adjusting the tracking. This new feature of ROI autocentre means that as the target drifts out to the edge of FOV, it would recentre itself.<\/p>\n

Amazing! This would work for at least 10-15 runs that I have tested so far. The limiting factor is when you run out of chip completely.
\nSo.. the summary is:
\ninitial starting performance with my setup for Jupiter imaging:
\nCelestron C9.25, x1.5 barlow, ZWO ASI585MC
\nusb cable3m,
\nHP Mini elitedesk 800 G3 computer
\nIntel Core I5-6500T; 16GB DDR4; Intel HD Graphics 530; Windows 10 pro 64 bit;
\n480GB nvme ssd; gigabit ethernet; USB 3.0
\n.SER file format
\nfirecapture buffer enabled<\/p>\n

Two extreme examples, image ID #138 and 136:
\nCase #1: Full resolution 120second run at 3.5ms exposure hit 47 fps got 5582 frames at 16% efficiency. Using the best 10% in autostakkert! Gave me 558 frames which is a pretty low signal to noise ration giving a notsogreat image quality.
\nCase #2: Last nights test of ROI 400×400, autocentering, cutout box of 400×400 hit 220fps giving 26091 frames at 77% efficiency. Using the best 10% to stack gives me 2609 frames, 4 times more signal to noise than before.
\nLooking at the images themselves<\/p>\n

Case#1
\n

\"\"<\/a>
copyright StarlightCascade Observatory<\/figcaption><\/figure>
\n\"\"<\/a><\/p>\n

\"\"<\/a><\/p>\n

Case#2
\n

\"\"<\/a>
copyright StarlightCascade Observatory<\/figcaption><\/figure>
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Looking at the images zoomed in a lot, Case#2 image is superior with much less noise resulting from the increased frame rate and more frames to stack as signal. Smaller ROI and cutouts are in fact better!<\/p>\n

These were taken in poor seeing and poor transparency and a lot of wind and wind gusts. I really hope to test this again under much better seeing conditions!
\nThere is still more work to do and maybe gain a little more efficiency.<\/p>\n

There are potential bottlenecks still:
\nUsb3.0 data rate vs camera output
\nusb cable quality and length
\nusb port on computer
\nusb bus inside computer
\ndata rate to drive (nvme faster than sata)
\ncomputer cpu and ram<\/p>\n

USB cables are the bane of imagers… having spares and testing\/swapping them out may have large effects.<\/p>\n

Ensure that the usb port you are using for the camera is used by nothing else (ie a hub with a usb2 keyboard or mouse connected as well). Those will slow down the bus rate and the camera will be affected.<\/p>\n

There are few planetary images in our Centre… so most of this article may not be of interest to you. Now. It will make a great reference in the future if you do enter into planetary imaging!<\/p>\n","protected":false},"excerpt":{"rendered":"

Lucky imaging, Firecapture, ROI and cutouts Planetary Imaging took a Quantum Leap with the advent of Lucky Imaging and digital cameras. Lucky imaging is the process of taking thousands of very short (millisecond) exposures, analyzing them, taking the best x% and stacking them to get a great signal to noise ration and images that surpass […]<\/p>\n","protected":false},"author":3,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[6],"tags":[],"class_list":["post-10891","post","type-post","status-publish","format-standard","hentry","category-astronomy"],"_links":{"self":[{"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/posts\/10891","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/comments?post=10891"}],"version-history":[{"count":3,"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/posts\/10891\/revisions"}],"predecessor-version":[{"id":10903,"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/posts\/10891\/revisions\/10903"}],"wp:attachment":[{"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/media?parent=10891"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/categories?post=10891"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/starlightcascade.ca\/blog\/wp-json\/wp\/v2\/tags?post=10891"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}