PERF: remove_unused_levels is very slow
#### Code Sample

```python
import numpy as np
import pandas as pd
series = pd.DataFrame(dict(
    A=np.random.randint(0, 10000, 100000),
    B=np.random.randint(0, 10000, 100000),
    V=np.random.rand(100000))).groupby(['A', 'B']).V.sum()
filtered_series = series[series < 0.1]
%time x = filtered_series.index.remove_unused_levels()
%time y = filtered_series.reset_index().set_index(['A', 'B']).index
```
#### Problem description

On my laptop, `x` takes 20 to 40 times as long as `y`, despite `y` doing the extra work of sorting the second level and reindexing the series in the process. The outputs, except for the sorting of the second level, are identical. Why is `remove_unused_levels` so slow?

#### Expected Output

`remove_unused_levels` should be at least as fast on large indexes as the `reset_index`/`set_index` hack.

#### Output of ``pd.show_versions()``
```
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.1.final.0
python-bits: 64
OS: Linux
OS-release: 4.11.2-1-ARCH
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: en_US.utf8
LOCALE: en_US.UTF-8

pandas: 0.20.1
pytest: None
pip: 9.0.1
setuptools: 35.0.2
Cython: None
numpy: 1.12.1
scipy: 0.19.0
xarray: None
IPython: 5.3.0
sphinx: None
patsy: None
dateutil: 2.6.0
pytz: 2017.2
blosc: None
bottleneck: None
tables: 3.4.2
numexpr: 2.6.2
feather: None
matplotlib: 2.0.0
openpyxl: None
xlrd: None
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.5.3
html5lib: None
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: None
pandas_gbq: None
pandas_datareader: None
```