rio-pansharpen 0.1.0

# rio-pansharpen

pansharpens Landsat 8 scenes.

## What is pansharpening?

Pansharpening is a process of using the spatial information in the high-resolution grayscale band (panchromatic, or pan-band) and color information in the multispectral bands to create a single high-resolution color image.
```
P pan-pixel cluster + M single multispectral pixel = M pan-sharpened pixel
```

Find more examples and information in the [Mapbox pansharpening blog post](https://www.mapbox.com/blog/l8-pansharpening/).

## Install

We highly recommend installing in a virtualenv. Once activated,
```
pip install -U pip
pip install rio-pansharpen
```

Or install from source
```
git checkout https://github.com/mapbox/rio-pansharpen.git
cd rio-pansharpen
pip install -U pip
pip install -r requirements.txt
pip install -e .
```

## Python API

### `pansharpen.worker`
The `worker` module pansharpens Landsat 8. Visit the [USGS Landsat page](http://landsat.usgs.gov/band_designations_landsat_satellites.php) page for more information on Landsat 8 band designations.

#### 1. `worker.pansharpen`
The `worker.pansharpen` function accepts the following as inputs:
- numpy 3D array with shape == (3, vis_height, vis_width)
- affine transform defining the georeferencing of the vis array
- numpy 2D array with shape == (pan_height, pan_width)
- affine transform defining the georeferencing of the pan array
- pansharpening method

and outputs:
- numpy 3D array with shape == (3, pan_height, pan_width)

```
>>> from pansharpen import worker
>>> from pansharpen.methods import Brovey
...
>>> pansharpened = worker.pansharpen(vis, vis_transform, pan, pan_transform,
pan_dtype, r_crs, dst_crs, weight,
method="Brovey", src_nodata=0)

```

#### 2.`worker.calculate_landsat_pansharpen`
```
>>> from pansharpen import worker
>>> from pansharpen.utils import _calc_windows
>>> import riomucho
...
>>> worker.calculate_landsat_pansharpen(src_paths, dst_path, dst_dtype,
weight, verbosity, jobs, half_window,
customwindow)
```

## `CLI`

### `pansharpen`

```
Usage: pansharpen [OPTIONS] [SRC_PATHS]... DST_PATH

Pansharpens a landsat scene. Input is a panchromatic band (B8), plus 3 color
bands (B4, B3, B2)

pansharpen B8.tif B4.tif B3.tif B2.tif out.tif

Or with shell expansion

pansharpen LC80410332015283LGN00_B{8,4,3,2}.tif out.tif

Options:
--dst-dtype [uint16|uint8]
-w, --weight FLOAT Weight of blue band [default = 0.2]
-v, --verbosity
-j, --jobs INTEGER Number of processes [default = 1]
--half-window Use a half window assuming pan in aligned with
rgb bands, default: False
-c, --customwindow INTEGER Specify blocksize for custom windows >
150[default=src_blockswindows]
--help Show this message and exit.
--help Show this message and exit.
```

## Comparison of Different Pansharpening Methods

We've implemented the Weighted Brovey Transform for pansharpening, which is appropriate for data like Landsat where the panchromatic band is relatively similar in resolution to the color bands.

For more information on other pansharpening methods such as IHS, PCA, P+XS, Wavelet, VWP, Wavelet with Canny Edge Detector etc, please read our notes [here](https://github.com/mapbox/pansharpening/blob/master/docs/pansharpening_methods.md).