Dictionary-based compression is based on prediction that recently seen words will be used again. That happens to be generally true for lots of datasets, including human languages (zipf distribution).

JPEG's zig-zag is a primitive for quantization, throwing data away based on rough approximation of human perception and biology. That isn't compression itself. However, the rounded and zeroed-out data is then compressed using a combination of RLE and Huffman, set up to predict the data will have lots of zeroes and few other distinct values (which the earlier step forces to be true). Or if you think about the system as a whole, you could say that JPEG predicts images will be blocky low-frequency patterns of DCT.

> dictionary based compression

That corresponds to PCFG models.