Study on Image Quality Assessment with Scale Space Approach Using Index of Visual Evoked Potentials

Abstract

This chapter presents an objective assessment method of image quality using visual evoked potentials (VEPs) to image engineer field based on multi-disciplinarily approach such as knowledge of neurobiology, image recognition theory, or computer vision. The multi-disciplinarily based objective assessment method applies Gaussian scale-space filtering in order to define a scalar parameter to depict blur image. In the experiment, visual stimuli are provided by the scalar parameter, and subjects are detected using VEPs. Their VEPs are recoded during observation of the checkerboard pattern reversal (PR) stimuli, and are analyzed with a latency of about Negative 145 msec (N145) component. The result of the experiment was that latency of N145 components were long about10-20 msec when parameters were large vale (more blur). This result shows one example of availableness for the multi-disciplinarily based objective assessment of image quality by integrating the pattern reversal visual evoked potential (PR-VEP) and the scale-space theory.