Images possess not only abundant visual content but also inherent high-level semantics,rendering them a pivotal medium for information transmission.Measuring the information of images is an abstract process of qualitative description and quantitative calculation of image information,constituting a fundamental aspect of scientific theories in the field of image processing.While the measurement of"image information"has been mentioned in previous research,it primarily centers on the quality or features of images,neglecting the exploration of the factors linked to high-level semantics and human cognition.Hence,to gauge the informational value that images offer to individuals,this paper seeks to measure image information by modeling the iconic memory associated with individuals'"prior knowledge"and extracting image features pertinent to"the given tasks".This approach is grounded in the widely accepted belief that"the information of images differs among individuals and across various tasks".Firstly,a theoretical framework for measuring the information of images is proposed.It is demonstrated as follows:under the assumptions of"having access to all images in the world"and"possessing a feature that can fully express the semantic content of images",a hypersphere is constructed to describe the density of the neighborhoods of the sample point.By modeling the probability of semantic information within this framework,the information of images is obtained based on information theory under the theoretical assumptions.Secondly,the practical scenarios when the assumptions specified in the theoretical framework are not feasible are discussed.It is illustrated by reducing the assumption of"having access to all images in the world"to"the given specific dataset"and reducing the assumption of"possessing a feature that can fully express the semantic content of images"to"the given task-related features".Then the experiments were conducted to show how to effectively obtain numerical results of image information in practical scenarios using the proposed method.Lastly,the limitations of the measurement method and the boundaries of the measurement results are pointed out,and feasible directions for enriching and improving the relevant systems in the future are contemplated.
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