Frequency-tuned　saliency　detection　analyzes　image　saliency　from　the　perspective　of　frequency　domain　and　fully　combines　image　segmentation　method,　which　outputs　well-defined　boundaries　of　salient　objects.　However,　the　method　ignores　spatial　relationships　across　image　parts.　This　paper　proposes　an　improved　saliency　detection　method　on　the　basis　of　the　frequency-tuned　method.　In　this　method,　we　first　segment　the　input　image　into　regions　and　then　analyze　the　image　from　the　frequency　domain.　After　that,　we　preprocess　it　using　Gaussian　filter　to　eliminate　noise　and　coding　artifacts.　For　each　region,　we　can　get　saliency　map　in　region-level　based　on　region　contrast.　Finally,　salient　regions　are　selected　by　＂　winner-take-all＂　(WTA)　neural　network　and　Inhibition　of　Return(IOR)　mechanism.　The　proposed　salient　region　detection　algorithm　combines　the　virtues　of　frequency-tuning　and　region　contrast.　The　experimental　results　show　the　feasibility　and　validity　of　this　algorithm.