-
Posts
36,510 -
Joined
-
Last visited
-
Days Won
192
Content Type
Profiles
Forums
Gallery
Events
Blogs
Everything posted by michael.h.f.wilkinson
-
Dew on triplet refractors
michael.h.f.wilkinson replied to Richard136's topic in Getting Started General Help and Advice
I haven't had any real issues with my APM 80mm F/6 triplet. I do not have a dew heater (should get one), but dew always first builds up on the outer surface, so imaging is curtailed when that happens (which is rare, given the deep lens hood). When I bring the kit inside, the front element does generally fog up, but I only store it in its case once all signs of dew have disappeared. I have had this scope for about 8 years without any issues. -
New member of the 100 club
michael.h.f.wilkinson replied to Fellside's topic in Discussions - Scopes / Whole setups
Very nice set-up -
I have had similar issues with a secondary that had astigmatism when glued and none when hung from the perimeter (this on a much smaller scope), so I guess the gluing can put some strain on the glass
- 248 replies
-
- 2
-
- diy telescope
- imager
-
(and 2 more)
Tagged with:
-
I used the ASI183MC cropped down to roughly the sensor size of the ASI178m and took some longer SER files (2000 frames) to see if I could improve the detail. These are all stacks of 250 frames (using AS!3), B&W version sharpened in ImPPG, colour balance of colour version restored in Registax 6, colour and sharpened B&W version L+RGB combined in FITSwork, and final tweaks in GIMP Plato, Sinus Iridium, and environs Saturation pushed once: Twice: Copernicus and environs: Saturation pushed once: Twice: Thrice: Four times: Tycho and environs: Saturation pushed once: Twice: Thrice: Four times: Best seen at full resolution
- 1 reply
-
- 6
-
Although seeing was pretty atrocious, I managed to stack 100 frames out of 13 500-frame SER files captured with the C8 and ASI183MC camera. Not entirely pleased with the noise, but given the seeing I think this is just about as good as I could get it. Natural colour: Saturation pushed once: The background needs some leveling, I see, but clicking on the images for full resolution is recommended nonetheless
- 1 reply
-
- 3
-
Low power eyepiece - Fast 10” dob
michael.h.f.wilkinson replied to davhei's topic in Discussions - Eyepieces
I have the Nagler 31T5 and it is indeed a beast. I also have the Nagler 22T4, which is my main galaxy hunting EP, and a wonderfully comfortable EP to use. I have used it in Olly's 20" F/4.1 Dob, and it performed magnificently. It is a lot lighter than the 31T5 (a.k.a. "Panzerfaust"). -
M31, First LRGB image
michael.h.f.wilkinson replied to Danjc's topic in Getting Started With Imaging
Very nice detail captured. The core does look a little pink on my monitor, but that could easily be corrected with some tweaks -
I had a go at reprocessing the data obtained last Tuesday. I had one hour of data with the Canon EOS 550D, and one hour from the ASI183MC, both taken with the same scope (APM 80mm F/6 with 0.6x reducer. I merged the data with Astro Pixel Processor, cropped the result, and tweaked the output with GIMP. Quite pleased with the result, which is definitely less noisy than each of the single outputs. The ASI183MC clearly has the edge in sensitivity and resolution, but the additional hour's worth of data from the 550D definitely helps. Still some gradients there. Next time I will see that I get the flats sorted out properly S
-
M33 with the ASI183MC
michael.h.f.wilkinson replied to michael.h.f.wilkinson's topic in Imaging - Deep Sky
I did my best to mask the artefacts by darkening the background. Apparently, my cunning plan has worked -
Good news! Clouded here, alas
-
First deep-sky attempt with the ASI183MC, APM 80 mm F/6 triplet, and 0.6x focal reducer. I used the ZWO Mini-EFW with L-band filter to reach (roughly) the right distance from flattener to the sensor. This results of 1h worth of 30s lights, 20 darks and 40 flats. As can be seen I had problems with the original set of flats I got, so took new ones, but there are still some annoying gradients I cannot seem to get rid of. Star shapes are not that good in the outer parts. I must definitely look at the spacing again. Cropped, the result is noisy, but OK for just 1h
-
First M33 image, and first image using the 0.6x focal reducer on my APM 80mm F/6 triplet. I used the Canon EOS 550D. This is just 30 subs of 120s at ISO 800, with 20 flats and 20 darks. This is quite noisy (unsurprisingly, for just 1 h of data), and I don't like the star shapes that much. I might need to adapt the distance to the sensor a bit. I also have data grabbed with the ASI183MC with the same optics, but I am still processing those
- 1 reply
-
- 2
-
Interesting Filament, Convection Cells | Oct 23rd 2019
michael.h.f.wilkinson replied to MalVeauX's topic in Imaging - Solar
Great set of images and lovely set-up -
Yay! Imaging at last!
michael.h.f.wilkinson replied to michael.h.f.wilkinson's topic in The Astro Lounge
Same here. Over 45 subs grabbed, and still going strong -
Got the EQ3-2 with Canon EOS 550D and 200 mm telephoto out clicking away. I have got 120s unguided working neatly. Doing 60 subs on NGC 7000. After this I will have a go at M33 with the scope.
-
Will be drinking tea out of a new mug
michael.h.f.wilkinson replied to michael.h.f.wilkinson's topic in The Astro Lounge
I prefer to make my tea from proper boiling water using loose leaf Keemun black tea (祁门, although I sometimes go for Lapsang Souchong (正山小種)) in a mug of the same proportions as used by my Chinese colleagues. No milk or sugar. -
Will be drinking tea out of a new mug
michael.h.f.wilkinson replied to michael.h.f.wilkinson's topic in The Astro Lounge
Indeed it is -
- 10 replies
-
- 23
-
Actually, I tend to prefer statistical approaches to machine learning in this context. Our MTObjects program has shown that you can achieve high recall and precision just by detecting features for which the null hypothesis that the structure is noise must be rejected at the p=10^-6 level, without any assumptions on what sort of structure it is. With machine learning you run the risk that the method will find those structures it has been taught to find, and potentially ignore interesting new stuff. Our adaptive blurring filters are also being optimised by looking at the relationships with optimal kernel density estimation (after all, we want to estimate the density distribution of photons in the image optimally) .Machine learning can and will be used to do a classification of objects into known classes, preferably with an extra class label "Human help needed" for things that look like they don't fit into any known category well.