NoiseChisel was initially introduced in Akhlaghi and Ichikawa  and updates after the first four years were published in Akhlaghi . To help in understanding how it works, those papers have many figures showing every step on multiple mock and real examples. We recommended to read these papers for a good understanding of what it does and how each parameter influences the output.
However, the papers cannot be updated anymore, but NoiseChisel has evolved (and will continue to do so): better algorithms or steps have been found and implemented and some options have been added, removed or changed behavior. This book is thus the final and definitive guide to NoiseChisel. The aim of this section is to make the transition from the papers above to the installed version on your system, as smooth as possible with the list below. For a more detailed list of changes in each Gnuastro version, please see the NEWS file175.
It was possible to play with the parameters to correct this for that particular dataset, but that was frustrating. Therefore from version 0.14, instead of finding outliers from the full tile distribution, we now measure the slope of the tile’s nearby tiles and find outliers locally. For more on the outlier-by-distance algorithm and the definition of slope, see Quantifying signal in a tile. In our tests, this gave a much improved estimate of the quantile thresholds and final Sky values with default values.