A starshade is a promising instrument for the direct imaging and characterization of exoplanets. However, even with a starshade, exoplanets are difficult to detect because detector noise, starshade defects, and misalignment (dynamics of the starshade system) degrade the signal to noise ratio (SNR) and contrast. No image processing methods have been specialized for images produced by a starshade system (simply referred as starshade images later). In this paper, we present a method, based on the generalized likelihood ratio test (GLRT), to detect and characterize planets from a single starshade image or multiple starshade images. This paper describes the GLRT model and its preliminary results for simulated images with starshade shape error, dynamics, detector noise and starshade rotation considered. The planets are detected with low false alarm rate, and planet positions are accurately estimated, and planet intensities are reasonably estimated. Thus, it demonstrates great potential as an acute and robust detection method for starshade images.