In　this　paper,　a　semantic　model　-　IISM　(image　internal　semantic　model)　is　introduced.　Unlike　other　semantic　extracting　methods,　IISM　extracts　the　semantic　information　not　by　image　segmentation　and　image　understanding,　but　by　analyzing　relevance　feedback　image　retrieval　results.　For　relevance　feedback　image　retrieval　system,　the　images　relevant　to　query　are　pointed　as　positive　example,　otherwise　the　images　irrelevant　to　query　are　pointed　as　negative　examples.　It　is　assumed　that　these　positive　examples　are　related　in　semantic　content.　IISM　computes　comprehensive　pair-wise　mutual　information　for　all　images　through　analyzing　the　results　of　relevance　feedback　image　retrieval.　An　association　with　a　high　mutual　information　means　that　one　image　is　semantically　associated　with　another.　Semantic　retrieval　and　clustering　is　carried　out　based　on　these　association　relationships.