The invention discloses a multi-
algorithm fusion method for bimodal
infrared image difference characteristic index measurement. The multi-
algorithm fusion method comprises the following steps that: firstly, selecting difference characteristic types between
infrared polarization and a
light intensity image, wherein the difference characteristic types are mainly luminance, details, edges, outlines and the like; according to the difference characteristic types, selecting local
energy maximization, non-subsampling shear wave and multiscale guidance filtering to independently carry out fusion on a
source image; independently calculating the local mean value, the local Laplacian energy and the local standard deviation of two classes of image; utilizing the local mean value, the local Laplacian energy and the local standard deviation of two classes of image to calculate each difference characteristic index measurement; and constructing a difference characteristic index measurement
covariance matrix, calculating the feature value and the
feature vector of the
covariance matrix, and selecting the
feature vector corresponding to a maximum feature value as each
algorithm weight to keep the function of the edge and the outline feature of the
high luminance, multiple details and
high definition of
infrared polarization and
light intensity images while multiple algorithms are fused while multi-algorithm fusion is realized. Therefore, the fusion effect of multi-algorithm fusion can be obviously improved.