A deep-sky object only photographs well when it actually fits inside your camera’s field of view with a little room to spare. This calculator combines your sensor size, focal length, and the target’s catalog angular size to tell you the field of view, how much of the frame the object fills, which way to turn the camera, and your image scale.
How it works
Field of view comes from the sensor dimensions and focal length, and image scale comes from the pixel pitch:
FOV (deg) = 2 × atan(sensor_mm / (2 × focal_length_mm)) × 180/π
FOV (arcmin) = FOV (deg) × 60
fill (width) = target_width_arcmin / FOV_width_arcmin
fill (height) = target_height_arcmin / FOV_height_arcmin
image scale ("/px) = 206.265 × pixel_size_µm / focal_length_mm
The width and height are evaluated independently, then the tool checks both the upright orientation and a 90° rotation to see which one frames the target’s long axis along the sensor’s long axis.
Example
An APS-C sensor (23.5 × 15.6 mm) at 530 mm focal length gives a field of view of roughly 152 × 101 arcminutes. The Andromeda Galaxy at 178 × 63 arcminutes overfills the width in landscape but fits comfortably when the camera is rotated to portrait — exactly the kind of decision this tool surfaces.
Understanding fill percentage
The fill percentage tells you what fraction of the sensor’s width or height is covered by the target object. Different fill levels suit different imaging goals:
- Under 30% — the object is small in the frame. Consider a longer focal length, or plan to crop heavily in post-processing. Some imagers deliberately shoot wide and crop to have framing flexibility.
- 40–75% — a comfortable working range. There is enough margin on all sides for drift, field rotation during a long session, and dithering between frames.
- 80–90% — tight framing. The object fills most of the sensor. This can be visually striking but leaves little margin for guiding drift or polar alignment error to work with. Align carefully.
- Over 100% — the object is larger than your field of view. A mosaic is needed: multiple overlapping frames stitched in post-processing. The most common targets requiring mosaics are the Andromeda Galaxy (for a portrait orientation at moderate focal lengths) and large nebulae like the North America Nebula.
Image scale and sampling
The image scale output (206.265 × pixel_size_µm / focal_length_mm) tells you how many arcseconds of sky each pixel covers. This matters because:
- Under-sampling (too many arcseconds per pixel): detail that exists in the sky is blurred into a single pixel, wasting resolving power. Generally anything over 3–4 arcsec/px is coarse for typical deep-sky detail.
- Over-sampling (too few arcseconds per pixel): each pixel covers less sky than your atmospheric seeing allows you to resolve. The image looks spread out, noise is higher per unit of signal, and file sizes are large without a detail benefit. Under typical UK or suburban seeing of 2–4 arcseconds, an image scale of 1–2 arcsec/px is usually appropriate.
Most deep-sky imagers target 1–2 arcseconds per pixel for galaxy imaging and can tolerate 2–3 arcsec/px for large bright nebulae where fine detail is less critical.
Finding angular sizes for catalog objects
The Messier and NGC catalogs list each object’s apparent size in arcminutes. Some commonly imaged objects and their approximate angular sizes:
| Object | Type | Angular size (arcmin) |
|---|---|---|
| M31 (Andromeda) | Galaxy | 178 × 63 |
| M42 (Orion Nebula) | Nebula | 85 × 60 |
| M45 (Pleiades) | Cluster | 110 |
| M57 (Ring Nebula) | Planetary | 1.4 × 1.0 |
| NGC 7293 (Helix) | Planetary | 28 × 23 |
Note that visual catalogs often list the bright core size; faint outer structure extends further and may benefit from a wider field than the catalog size suggests.
Tips
Keep your fill under about 80 percent so polar-alignment drift and field rotation do not crop the object during a long imaging session. Use the image-scale output to avoid heavy oversampling on short focal lengths. And check both landscape and portrait orientations — rotating the camera 90° can make the difference between a mosaic and a single-panel image.