关键词: 显著性目标检测, 幂律变换, IG算法, LC算法, 自适应图像增强

Abstract: To solve the problem that the salient detection method has low contrast, the object area is not obvious, the detection area is not accurate, and the background suppression effect is insufficient. The power object transformation and IGLC algorithm are proposed. First, the power law transformation function is used to optimize the IG algorithm to completely suppress the background area of the saliency map. The binarized saliency map is segmented in the original image to obtain the segmentation map of the object of interest. Secondly, the LC algorithm optimizes the segmentation map of the object of interest to obtain the saliency map with good detail. Finally, the adaptive fireworks algorithm is used to enhance the contrast of the salient object region, generating the final saliency map. The object test of the standard test dataset MSRA10K and PASCAL-S datasets is performed, and subjective and objective comparison analysis is carried out with the six popular object detection methods. The analysis results are superior to the comparison methods. The salient map obtained by the algorithm has the advantages of contrast and detail enhancement, and has better background suppression effect.

Key words: salient object detection, power law transform, IG algorithm, Luminance Contrast（LC）algorithm, adaptive image enhancement