Pulse-coupled　neuron　networks　(PCNN)　can　be　efficiently　applied　to　image　segmentation.　However,　the　performance　of　segmentation　depends　on　the　suitable　PCNN　parameters,　which　are　obtained　by　manual　experiment,　and　the　effect　of　the　segmentation　needs　to　be　improved　for　images　with　noise.　In　this　paper,　dynamic　mechanism　based　PCNN(DMPCNN)　is　brought　forward　to　simulate　the　integrate-and-fire　mechanism,　and　it　is　applied　to　segment　images　with　noise　effectively.　Parameter　selection　is　based　on　dynamic　mechanism.　Experimental　results　for　image　segmentation　show　its　validity　and　robustness.