关键词: 图像质量客观评价, 清晰度评价函数, 图像边缘, 信息熵, 通用评价能力

Abstract: Image Quality Assessment（IQA） has long been a hot topic in the research field of computer vision. It is still a hard-tackling problem to enable the computer to assess the image quality as human visual system. As a vital component of IQA, Image Definition Evaluation Function（IDEF） is not only of great significance, but also conductive to the development of the related fields such as image restoration and image enhancement. The current IDEFs are mainly based on the amount of the image edge information or overall information entropy to estimate the image’s definition. This paper discusses the general evaluation efficiency of five typical IDEFs, and aims to study on their effectiveness to evaluate the definition of different images blurred in different depth simultaneously, which will indicate the distance between the given five IDEFs and the subjective perception.

Key words: image quality assessment, image definition evaluation function, image edge, information entropy, general evaluation efficiency