Extracting Compact Information from Image Benchmarking Tools: The SAR Despeckling Case

Image databases and benchmarks are precious tools to assess the quality of competing algorithms and to fine tune their parameters. In some cases, however, quality cannot be captured by a single measure, and several of them, providing typically contrasting indications, must be computed and analyzed. This is certainly the case for the SAR despeckling field, also because of the lack of clean reference images, which forces one to compute the measures of interest on simple canonical scenes. We present here the first results of an ongoing work aimed at selecting a suitable combination of benchmark measures to assess competing SAR despeckling techniques and rank them. The full validation of the proposed methodology will require the involvement of a reasonable number of expert photo-interpreters for a large-scale experimental campaign. Here, we present only a sample experiment to provide some insight about the approach.