Abstract: A method for generating a cloud free and cloud-shadow free image from a plurality of images of a region, the method including the steps of ranking pixels in order of cloudiness and shadowness, generating cloud and shadow masks by classifying a group of pixels as cloud, shadow, or noncloud-nonshadow, and creating a mosaic from the plurality of images to form the cloud free and cloud-shadow free image.

Abstract: An RPC camera model is applied to a set of intermediate object-space coordinates, where the intermediate object-space coordinates are determined by scaling, translating and rotating original object-space coordinates. The resulting image-space coordinates may be seen to more accurately remove residual error or bias that may exist for one or more of the imaging parameters on which the RPC camera model is based. The RPC camera model thus refined may then be used for photogrammetric processing of associated satellite imagery, including block adjustment, 3D feature extraction and orthorectification. Alternatively, a new RPC camera model (i.e., new coefficients) may be determined based on scaling, translating and rotating parameters. The new RPC camera model may then be applied to the original object-space coordinates to determine image-space coordinates.