When you talk about maximizing compression, you usually move from simple binary data to predictors.
A predictor is where you look at pixel above, and pixel to the left, and instead of coding a raw pixel value, you sort the values by how likely they are for the given "above" and "left" values. Most likely value becomes 0, second most likely becomes 1, etc... This changes the image into a different image where you have more 0 values than others. So you can encode the data as "number of 0s", like RLE, but with the zero count encoded in a variable-length way.
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When you talk about maximizing compression, you usually move from simple binary data to predictors.
A predictor is where you look at pixel above, and pixel to the left, and instead of coding a raw pixel value, you sort the values by how likely they are for the given "above" and "left" values. Most likely value becomes 0, second most likely becomes 1, etc... This changes the image into a different image where you have more 0 values than others. So you can encode the data as "number of 0s", like RLE, but with the zero count encoded in a variable-length way.