We present the progress in developing methods for validation of computer programs for prediction of optical signatures. The work is currently performed in two directions: The first is concerned with developing methods for quantifying the propagation of input data uncertainties to output parameters (i.e. radiance or temperature) in computational predictions. The objective of the second path of development is to analyze and validate the differences between simulated and measured images, for instance in the visual or IR, through image features such as statistical moments and Gabor wavelets. In particular, aspects that are important for detection, classification and identification of targets are considered. The work on propagation of uncertainties in computational predictions has resulted in a number of proposed methods. In this report we present a first test case using the error propagation method. The results are according to expectations but it is concluded that further studies, using a more general method, is desirable to assess the results. In the work on analyzing differences between simulated and measured images it is proposed that several textural features are used to define the discriminative capability when it comes to detect vehicles in a terrain. In a preliminary example, several feature values have been computed for a measured image and the corresponding simulated image. This work will continue during 2005.