Extraction method of visual salient regions based on multiscale relative entropy

The invention discloses an extraction method of visual salient regions based on multiscale relative entropy. The extraction method of the visual salient regions based on the multiscale relative entropy comprises extracting different global color feature characteristic patterns and direction characteristic patterns from input images, carrying out gaussian pyramid decomposition and multiscale normalization on the global color feature characteristic patterns and the direction characteristic patterns, respectively computing color partial relative entropy and direction partial relative entropy of respective feature space, respectively normalizing results of the different feature space, carrying out linearity superposition of the results of the different feature space, linearly adding color saliency maps and direction saliency maps together, carrying out two-dimensional gaussian smoothing, and therefore extracting visual salient regions. Compared with a traditional method, the extraction method of the visual salient regions based on the multiscale relative entropy takes a full account of color features and direction features reflecting global significance and relative entropy reflecting partial novelty, adopts a method of multiscale analysis, and has the advantages of being effective and reliable. The extraction method of the visual salient regions based on the multiscale relative entropy is capable of being used for self-adaption compressed sampling and target detection of natural images, remote sensing images and the like, and is wide in application prospect of lowcost imaging devices.