METHOD FOR NO-REFERENCE IMAGE QUALITY ASSESSMENT

摘要

Aspects of the present disclosure are related to methods for automated image quality assessment without the use of a reference image. In some embodiments, quantitative measurements for specific artifacts that impact image quality such as blurriness, noisiness and blockiness (BNB) metrics are used to form a vector to represent the quality of a given electronic image. Based on this vector, entries in a data structure are selected. In some embodiments, a k-Nearest Neighbors algorithm (k-NN) is used to map the vector of BNB metrics of the electronic image to a human perception score based on vector differences between the quantitative measurements for the electronic image and similar quantitative measurements for known images to which human perception scores have been assigned. The human perception scores for the selected entries in the data set may then be combined to yield a quality score for the electronic image, emulating a quality score that would be assigned by human image evaluators.