CloudClean.jl
Image infilling algorithm with focus on statistically accuracy
Installation
<!– CloudClean is a registered package so a stable version can be installed using Pkg.add.
import Pkg
Pkg.add("CloudClean")–> For the most recent development version, install directly from the GitHub
import Pkg
Pkg.add(url="https://github.com/andrew-saydjari/CloudClean.jl")Description
By leveraging the local pixel-pixel covarariance structure in an image, CloudClean attempts to predict the values of missing pixels based on near-by unmasked pixels. The user needs only to provide an image and a mask of "bad" pixels and the choice of a few hyper parameters. CloudClean has two main operating modes:
- proc_discrete, which attempts to fill in masked data in a subregion centered on a discrete list of input points
- proc_continuous, which infills arbitrarily shaped and centered masks. The latter is like "Photoshop" for images with correlated structure.
This code is based heavily upon (and is in some sense a simplification of) CloudCovErr.jl.
Example
An intial example is provided in a Jupyter notebook in the "examples" folder. More examples, notebooks, and documentation are in process.
Contributing and Questions
This is a new piece of software. Filing an issue to report a bug or request a feature is extremely valuable in helping us prioritize what to work on, so don't hesitate.