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In recent years, the research community has witnessed a growing interest in immersive representations of the real world, such as light field. However, due to the increased volume of data generated in the acquisition, new and efficient compression algorithms are needed to store and deliver light field contents. A Grand Challenge on light field image coding was organised during ICIP 2017 to collect and evaluate new compression algorithms for lenslet-based light field images. This paper reports the results of the objective and subjective evaluation campaign conducted to assess the responses to the grand challenge. An adjectival categorical rating methodology with 7-point grading scale was selected to perform subjective assessments, whereas the objective assessment was conducted using popular image quality metrics. Results show that two proposals have comparable performance and outperform the others across all bitrates.

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