Benchmarking real-life image processing programs in lazy functional languages

This paper presents our practical experience gained from writing image processing programs in lazy functional languages. We give some benchmarking results comparing median filter operations written in C, Mirandal and Haskell. (The median filter is a common method for removing noise from images.) Also, using a profiling tool, we achieve remarkable improvement of the Haskell code. In particular, we show that the Haskell program runs in constant space, which is difficult to achieve in C without extra programming effort. Although the performance of lazy functional language is beginning to make them feasible for specific purposes such as rapid prototyping, better compilers and tools are still needed to encourage wider use in image processing applications.

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