The recent advances in light field imaging, supported among others by the introduction of commercially available cameras e.g. Lytro or Raytrix, are changing the ways in which visual content is captured and processed. Efficient storage and delivery systems for light field images must rely on compression algorithms. Several methods to compress light field images have been proposed recently. However, in-depth evaluations of compression algorithms have rarely been reported. This paper aims at evaluation of perceived visual quality of light field images and at comparing the performance of a few state of the art algorithms for light field image compression. First, a processing chain for light field image compression and decompression is defined for two typical use cases, professional and consumer. Then, five light field compression algorithms are compared by means of a set of objective and subjective quality assessments. An interactive methodology recently introduced by authors, as well as a passive methodology is used to perform these evaluations. The results provide a useful benchmark for future development of compression solutions for light field images.