Reliable Shapelet Image Analysis

Abstract

Aims: We discuss the applicability and reliability of the shapelet technique for scientific image analysis. Methods: We quantify the effects of non-orthogonality of sampled shapelet basis functions and misestimation of shapelet parameters. We perform the shapelet decomposition on artificial galaxy images with underlying shapelet models and galaxy images from the GOODS survey, comparing the publicly available IDL implementation with our new C++ implementation. Results: Non-orthogonality of the sampled basis functions and misestimation of the shapelet parameters can cause substantial misinterpretation of the physical properties of the decomposed objects. Additional constraints, image preprocessing and enhanced precision have to be incorporated in order to achieve reliable decomposition results.