Quantifying interpretability for motion imagery: Applications to image chain analysis

The motion imagery community will benefit from the availability of standard measures for assessing image interpretability. The national imagery interpretability rating scale (NIIRS) has served as a community standard for still imagery, but no comparable scale exists for motion imagery. We conducted a series of user evaluations to understand and quantify the effects of critical factors affecting the perceived interpretability of motion imagery. These evaluations provide the basis for relating perceived image interpretability to image parameters, including ground sample distance (GSD) and frame rate. The first section of this paper presents the key findings from these studies. The second portion is a new study applying these methods to quantifying information loss due to compression of motion imagery. We conducted an evaluation of several methods for video compression (JPEG2000, MPEG-2, and H.264) at various bitrates. A set of objective image quality metrics (structural similarity, peak SNR, an edge localization metric, and edge strength) were computed for the parent video clip and the various compressed products. In an evaluation, imagery analysts rated each clip relative to image interpretability tasks. The analysis quantifies the interpretability loss associated with the various compression methods and bitrates. We present the evaluation results and explore their relationship to the objective image quality metrics. The findings indicate the compression rates at which image interpretability declines significantly. These findings have implications for sensor system design, systems architecture, and mission planning.