Laser speckle contrast imaging (LSCI) is an optical imaging method, which can monitor microvascular flow variation directly without addition of any ectogenous dye. All the existing laser speckle contrast analysis (LASCA) methods are a combination of spatial and temporal statistics. In this study, we have proposed a new method, Gaussian kernel laser speckle contrast analysis (gLASCA), which processes the raw images primarily with the Gaussian kernel operator along the spatial direction of blood flow. We explored the properties of gLASCA in the simulation and animal cerebral ischemia perfusion model. Compared with the other existing speckle processing methods based on spatial, temporal, spatial-temporal or anisotropic linear structure; the present gLASCA method has a high spatial-temporal resolution to respond the change of velocity especially in microvasculature. Besides, the gLASCA method obtains approximately 10.2% and 7.1% higher contrast-to-noise ratio (CNR) over the anisotropic linear method (aLASCA) in the simulation and experiment models. For these advantages, gLASCA could be a better method for local microvascular laser speckle imaging in terms of cerebral ischemia reperfusion, spreading depression and brain injury diseases.