extract-paper-images

Extracting publication-quality images from arXiv papers involves prioritizing original source assets over PDF figures to ensure maximum clarity. This automated process fetches authentic images directly from source packages, guaranteeing high-resolution outputs for literature reviews and notes.

Yes, if the arXiv source package is unavailable, the system automatically falls back to extracting figures directly from the local PDF file. This ensures you still retrieve the necessary images even without access to the original source assets.

The three-tier pipeline works by sequentially attempting arXiv-source image extraction, then PDF figure extraction, and finally raw PDF extraction. This prioritized approach ensures the highest available image quality while minimizing the capture of non-core elements.

Yes, PyMuPDF supports extracting publication-quality figures from scholarly articles by parsing PDF documents to locate and render images. It handles the PDF extraction fallback tier, ensuring reliable figure capture when source packages are inaccessible.

The best way to organize extracted paper figures for notetaking is to save them in a structured directory like Literature/images/[citekey]/ and generate an index file. This index maps sources, paths, and formats, streamlining integration into notes and dashboards.

PDF image extraction captures non-core elements because PDFs flatten documents into visual objects without semantic separation. Prioritizing arXiv source packages avoids this by fetching original figures directly from their designated directories, bypassing PDF rendering limitations.