
Hypergraphs are a very powerful tool and can represent many problems. In this paper we define a new image representation based on hypergraphs. This representation conducts to a new lossless compression algorithm for images called HLC. We present the algorithm and give some experimental results proving its efficiency. Finally we show that this algorithm can be generalized to three-dimensional images and to parametric lossy compression.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 1 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
