Abstract :
This paper describes image fusion in detail, and firstly intrudes the three basic levels which are pixel level, feature level and decision level fusion, and then compares with their properties and all other aspects. Then it describes the evaluation criteria of image fusion results from subjective evaluation and objective evaluation two aspects. According to the quantitative evaluation of the image fusion results and quality, this text uses and defines multiple evaluation parameters such as fusion image entropy, mutual information MI, the average gradient, standard deviation, cross-entropy, unite entropy, bias, relative bias, mean square error, root mean square error and peak SNR, and establishes the corresponding evaluation criteria.
Keywords :
image fusion; average gradient; cross-entropy; decision level fusion; feature level; image fusion entropy; mutual information; objective evaluation; peak SNR; pixel level; root mean square error; standard deviation; subjective evaluation; Cities and towns; Data mining; Entropy; Feature extraction; Image analysis; Image fusion; Image sensors; Information analysis; Pixel; Sensor fusion; image fusion; objective evaluation; pixel fusion; subjective evaluation;
