Image quality and image resolution

Abstract

A large effort has been made to characterize the image quality of remote sensing systems. One option is to use the National Image Interpretability Rating Scales (NIIRS), because NIIRS is re-lated to object detection. From an engineering standpoint NIIRS is not well suited, because it cannot be derived from the fundamental sensor and scene behaviour. An alternative approach is to derive an image quality criterion, based on the physical characteristics of sensor and scene. In this paper we present two approaches for physical based quality criteria. To assess the image quality, we compare the output of the real sensor with the output of an ideal sensor based on a Local Mean Squared Error (LMSE). This criterion, we abbreviate in the following with IQC (Image Quality Criterion). The second approach is a measure of the smallest resolvable object (SRO), which determines the size of a potential target to be imaged considering basic parameters of the opto-electronic system (e.g., ground sampling distance, signal-to-noise ratio, modulation transfer function, dynamic range). This criteria is related to the well known image resolution. SRO is a measure, which can be interpreted easily from users without being familiar with technical details on one hand, and is rather physics based than other heuristic models. SRO can be applied to all imaging optical sensor systems in an identical way avoiding different physical models or measures. In the paper, these approaches are discussed and compared. ...