I would encourage you not to give up too quickly. As Cliff pointed out, it isn't trivial to do this, but neither is it so difficult that it isn't worth trying (depending on how much you want the data). To demonstrate, I created & uploaded a tabulation for you that dimensionalizes every household in the 2014 PUMS file by HAMFI, using the breakouts that were in the link you provided (<30%, 30-50%, etc.). I used a two step process. First, I dimensionalized the family incomes (fincp) of all occupied households by PUMA (the smallest geographic area available in PUMS) and state (because PUMAs are duplicated across states). Then I used a spreadsheet to calculate the average income for each area (PUMA in this case, but the same could be done for other areas, such as states). Then I used that file to create a new variable (call it average area income) for every household.
In the second step, I created the tabulation that I uploaded, comparing each family income to the average for their PUMA (which I had derived in the first step), using the divisions that were in the link. If the PUMS file will work for you (meaning that PUMAs or geographies that can be made up from PUMAs are acceptable) I see no reason why this can't be done. The hardest part is probably creating the HAMFI, which I've already done if you are to use PUMAs. Things like kitchen and plumbing facilities are pretty trivial to include.
Caveat: After I did this, I realized that the 'M' in HAMFI is supposed to be the median, and I used the mean. I question the value of using the median in this case from the PUMS, because the family income is topcoded (so the mean is artificially set). At any rate, if you are interested in pursuing this & want to use the mean, it can be done. The thing to figure out first is whether or not PUMS geographies will work for you, and will the 2014 file be sufficient (it is the only single-year file that I have available).