Originally written by Jens Gulden — see AUTHORS for more information. Licensed under GNU GPL v2 — see COPYING for more information.

unpaper is a post-processing tool for scanned sheets of paper, especially for book pages that have been scanned from previously created photocopies. The main purpose is to make scanned book pages better readable on screen after conversion to PDF. Additionally, unpaper might be useful to enhance the quality of scanned pages before performing optical character recognition (OCR).

unpaper tries to clean scanned images by removing dark edges that appeared through scanning or copying on areas outside the actual page content (e.g. dark areas between the left-hand-side and the right-hand-side of a double- sided book-page scan).

The program also tries to detect misaligned centering and rotation of pages and will automatically straighten each page by rotating it to the correct angle. This process is called "deskewing".

Note that the automatic processing will sometimes fail. It is always a good idea to manually control the results of unpaper and adjust the parameter settings according to the requirements of the input. Each processing step can also be disabled individually for each sheet.

See further documentation for the supported file formats notes.

The only hard dependency of unpaper is libav, which is used for file input and output.

At the time of writing, any version of libav can be used, and at least from version 9 it supports a superset of the file formats supported by unpaper before version 6.

The yet to be released version 11 is recommended, once available, as it has better support for TIFF files, including a faster, less memory-consuming support for grayscale TIFF files, and support for grayscale and alpha files.

unpaper uses GNU Autotools for its build system, so you should be able to execute the same commands used for other software packages:

./configure
make
sudo make install

There are, though, some recommendations about the way you build the code. Since the tasks are calculation-intensive, it is important to build with optimizations turned on:

./configure CFLAGS="-O2 -march-native -pipe"

Even better, if your compiler supports it, is to use Link-Time Optimizations, as that has shown that execution time can improve sensibly:

./configure CFLAGS="-O2 -march=native -pipe -flto"

Further optimizations such as -ftracer and -ftree-vectorize are thought to work, but their effect has not been evaluated so your mileage may vary.

You can find more information on the basic concepts and the image processing in the available documentation.