It　is　ubiquitous　that　meaningful　structures　are　appear　over　textured　surfaces.　Extracting　them　under　the　complication　of　texture　patterns　is　very　challenging,　but　of　great　practical　importance.　Consequently,　we　have　proposed　a　novel　structure-aware　filter　via　bilateral　kernel　regression　with　a　variational　structure-kernel　descriptor　which　can　extract　main　structures　from　textures　through　variational　structure-kernel　descriptor　and　incorporate　its　results　into　the　bilateral　kernel　regression:　we　first　apply　the　related　reductive　texture　decomposition　to　construct　the　structure-kernel　descriptor.　Then,　we　incorporate　the　descriptor　into　the　bilateral　kernel　regression　to　achieve　an　expected　structure-preserving　output.　Algorithmically,　we　propose　a　numerically　stable　approximation　iterative　procedure　to　achieve　effective　implementation.　At　last,　some　experimental　results　are　presented　to　demonstrate　that　our　approach　leads　to　better　or　comparable　performance　and　is　effect　in　some　applications,　such　as　HDR,　super-pixel　segmentation　and　so　on.　©　2016,　Beijing　China　Science　Journal　Publishing　Co.　Ltd.　All　right　reserved.