For　the　limited　transmission　capacity　and　compressed　images　in　the　network　environment,　a　compressed-domain　image　filtering　and　re-ranking　approach　for　multi-agent　image　retrieval　is　proposed　in　this　paper.　Firstly,　the　distributed　image　retrieval　platform　with　multi-agent　is　constructed　by　using　Aglet　development　system,　the　lifecycle　and　the　migration　mechanism　of　agent　is　designed　and　planned　for　multi-agent　image　retrieval　by　using　the　characteristics　of　mobile　agent.　Then,　considering　the　redundant　image　brought　by　distributed　multi-agent　retrieval,　the　duplicate　images　in　distributed　retrieval　results　are　filtered　based　on　the　perceptual　hashing　feature　extracted　in　the　compressed-domain.　Finally,　weight-based　hamming　distance　is　utilized　to　re-rank　the　retrieval　results.　The　experimental　results　show　that　the　proposed　approach　can　effectively　filter　the　duplicate　images　in　distributed　image　retrieval　results　as　well　as　improve　the　accuracy　and　speed　of　compressed-domain　image　retrieval.