jpeg2fits Guide: Quick Steps for Astronomy Image ConversionConverting consumer image formats like JPEG into FITS (Flexible Image Transport System) is a common task in amateur and professional astronomy. FITS is the standard format for storing scientific image data because it supports precise pixel values, extended metadata (headers), multiple data extensions, and lossless representation of image data. JPEG, by contrast, is optimized for photographic display and typically uses lossy compression and 8-bit channels, which can make it unsuitable for direct scientific analysis. This guide walks through practical, reliable steps to convert JPEG images to FITS using jpeg2fits, explains why conversion matters, and covers tips for preserving useful data and metadata.

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Why convert JPEG to FITS?

• Preserve numerical precision: FITS supports higher bit depths and lossless storage of pixel values, which is important for photometry and precise measurements.
• Store metadata: FITS headers can hold telescope/instrument details, exposure time, observation date, and processing history in a standardized way.
• Compatibility: Most astronomy analysis tools (e.g., Astropy, IRAF, Maxim DL, PixInsight) work natively with FITS files.
• Scientific reproducibility: FITS makes it easier to document processing steps and retain original data provenance.

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When is conversion justified?

Conversion is appropriate when:

• You need to run photometric or astrometric measurements on images originally saved as JPEG.
• You want to archive images with richer metadata.
• You plan to use standard astronomy software that requires FITS.

Conversion cannot recover data lost to JPEG compression. If the original source is a RAW file (from a camera or specialized astronomy camera), convert that RAW to FITS directly when possible. JPEG-to-FITS is a rescue or interoperability solution, not a substitute for capturing in FITS/RAW.

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jpeg2fits: what it does

jpeg2fits is a utility (or a pattern of scripts/tools) designed to:

• Read JPEG images.
• Map JPEG pixel data (usually 8-bit RGB) into a FITS image array.
• Optionally combine RGB channels, convert to grayscale, or store each channel as a separate FITS extension.
• Create or populate FITS headers with user-supplied or extracted metadata (EXIF timestamps, camera model, GPS, exposure if present).
• Allow bit-depth conversion (e.g., promote to 16-bit or 32-bit floating) so downstream tools can operate without type limitations.

Different implementations of jpeg2fits exist (command-line tools, Python scripts based on Astropy, GUI wrappers). This guide focuses on general steps and an example Python-based workflow using common astronomy libraries.

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Prerequisites and tools

• A working Python environment (3.8+) or a tool that provides jpeg2fits functionality.
• Libraries: astropy, numpy, pillow (PIL), piexif or exifread (for extracting EXIF), optionally OpenCV.
• Basic familiarity with the command line and Python scripting.
• Example command-line jpeg2fits tools may be available for direct install; consult your distribution or the tool’s repository.

Install required Python packages:

pip install astropy numpy pillow piexif 

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Step-by-step conversion using a Python-based jpeg2fits workflow

Below is an organized sequence for converting JPEGs to FITS, with code snippets illustrating core steps (reading pixels, handling channels, promoting bit depth, and writing FITS with headers). This approach is flexible and can be adapted into a reusable script.

1. Read the JPEG and extract pixel data and EXIF metadata “`python from PIL import Image import piexif

img = Image.open(“image.jpg”) pixels = img.copy() # PIL Image object exif_dict = {} try:

exif_dict = piexif.load(img.info.get("exif", b"")) 

except Exception:

exif_dict = {} 

2) Decide how to map color channels - For single-channel analysis (luminance/monochrome), compute a weighted grayscale:   Y = 0.299 R + 0.587 G + 0.114 B - To preserve color, keep three extensions or a (3, H, W) data cube in FITS. 3) Convert to NumPy array and promote data type ```python import numpy as np arr = np.array(pixels)  # shape (H, W) for L mode or (H, W, 3) for RGB # Promote to 16-bit to avoid clipping in later operations if arr.dtype == np.uint8:     arr16 = (arr.astype(np.uint16) << 8) | arr.astype(np.uint16) else:     arr16 = arr.copy() 

1. Create FITS HDU(s) and populate header with EXIF and custom keys “`python from astropy.io import fits

hdu = fits.PrimaryHDU()

If grayscale:

if arr.ndim == 2:

hdu.data = arr16 

else:

# Create a 3D cube with shape (3, H, W) cube = np.transpose(arr16, (2, 0, 1)) hdu = fits.PrimaryHDU(data=cube) 

hdr = hdu.header

Example: copy some EXIF fields

if exif_dict:

dt = exif_dict.get("0th", {}).get(piexif.ImageIFD.DateTime) if dt:     hdr["DATEIMG"] = dt.decode() if isinstance(dt, bytes) else dt model = exif_dict.get("0th", {}).get(piexif.ImageIFD.Model) if model:     hdr["CAMMODEL"] = model.decode() if isinstance(model, bytes) else model 

hdr[“ORIGIN”] = “jpeg2fits” hdr[“COMMENT”] = “Converted from JPEG; original JPEG compression may have altered photometric fidelity.”

hdul = fits.HDUList([hdu]) hdul.writeto(“image.fits”, overwrite=True)

5) Validate output - Open the FITS file in DS9, SAOImage, or with astropy to confirm header fields and data orientation. - Check min/max pixel values and data type: ```python from astropy.io import fits with fits.open("image.fits") as hdul:     print(hdul[0].data.dtype, hdul[0].data.shape)     print(hdul[0].header) 

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Metadata considerations

• EXIF timestamps, camera make/model, focal length, and GPS (if available) are valuable. Map them into FITS header keys like DATE-OBS, TELESCOP, INSTRUME, FOCAL, and OBS-LAT/LONG.
• Record conversion provenance: add HISTORY or COMMENT cards describing the conversion tool and settings.
• Distinguish original camera exposure from any processing steps performed after JPEG creation.

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Handling color and Bayer data

• Consumer camera JPEGs are usually processed (demosaiced) and color-corrected. Demosaiced RGB is fine for visual inspection, but if you need sensor-level raw data, use RAW files (e.g., CR2, NEF) and convert them directly to FITS with raw conversion tools.
• If working with RGB for photometry, convert to grayscale using a luminance formula or keep channels separate and calibrate each channel individually.

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Batch conversion and automation

• For many images, write a script loop that:
  • Reads JPEG and EXIF.
  • Determines mapping (grayscale or cube).
  • Writes a FITS file with consistent headers.
  • Logs conversion successes/failures and summary stats (min/max values, saturation counts).
• Example pseudo-loop:

  
  for jpg in jpg_list: try:     convert_jpeg_to_fits(jpg, outdir) except Exception as e:     log_failure(jpg, str(e)) 

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Caveats and best practices

• JPEG compression artifacts: blockiness and quantization can bias faint-signal measurements. Treat results cautiously; verify against RAW/FITS originals when possible.
• Dynamic range: JPEGs are typically 8-bit per channel; expanding bit depth doesn’t restore lost dynamic range — it only prevents further loss during processing.
• Orientation and color profile: respect EXIF orientation and embedded color profiles when reading. Use libraries that honor these by default or correct orientation manually.
• Calibration frames: If you plan to calibrate (bias/dark/flat), ideally use matching RAW or FITS calibration frames. Calibrating a JPEG-based photometric pipeline is less robust.

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Example use cases

• Converting archived astrophotography JPEGs for cataloging and basic measurements.
• Preparing JPEG screenshots or web-downloaded images for alignment and visual stacking in FITS-capable tools.
• Teaching/exploration: converting sample JPEGs into FITS for students to practice header handling and basic analysis.

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Quick checklist before converting

• Confirm you need FITS for your analysis (tools or measurements require it).
• Prefer RAW-to-FITS if RAW originals exist.
• Extract and map EXIF metadata into FITS headers.
• Choose grayscale vs RGB cube based on analysis needs.
• Record conversion provenance in header HISTORY or COMMENT.
• Validate resulting FITS files visually and numerically.

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Further resources

• Astropy FITS documentation — for advanced header manipulation and FITS conventions.
• Camera RAW conversion guides — to avoid JPEG when sensor-level data are needed.
• FITS standard documents — for understanding header keyword conventions and best practices.

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Converting JPEG to FITS with jpeg2fits is practical and often necessary for interoperability, archiving, and basic scientific work on images originally saved in JPEG. Keep in mind the limitations imposed by JPEG’s lossy compression and 8-bit depth, and when possible, work from RAW or native FITS to preserve full scientific value.