For　human　face　images,　the　region　of　human　face　(ROHF)　is　considered　to　be　the　most　important　part,　while　the　background　is　allowed　to　have　degraded　quality　because　it　is　considered　to　be　less　important.　In　this　paper,　human　face　detection　algorithm　is　combined　with　the　set　partitioning　in　hierarchical　trees　(SPIHT)　algorithm　for　wavelet-based　image　coding.　The　human　face　detection　algorithm　is　employed　to　automatically　determine　the　ROHF　in　a　human　face　image.　The　ROHF　mask　is　generated　in　the　wavelet　domain.　The　wavelet　coefficients　in　the　ROHF　mask　of　the　LL　subband　are　scaled　to　ensure　that　they　are　encoded　with　a　higher　priority.　Finally　the　SPIHT　algorithm　is　directly　employed　to　encode　the　resulting　coefficients　progressively.　Experimental　results　show　that　the　ROHF　exhibits　much　better　quality　than　that　of　the　background　region　at　any　bit　rate.　The　encoded　bitstream　based　on　this　approach　is　fully　embedded　and　supports　progressive　transmission.