An Improved Computational Approach for Salient Region Detection

Salient region detection in images is very useful for image processing applications like image compressing, image segmentation, object detection and recognition. In this paper, an improved approach to detect salient region is presented. The proposed method can generate a robust saliency map and extract salient regions with precise boundaries. In the proposed method, local saliency, global saliency and rarity saliency of three kinds of low-level feature contrast of intensity, color and orientation are used to compute the visual saliency. A new feature integration strategy is proposed in this paper. This method can select features and compute the weights of the features dynamically by analyzing the effect of different features on the saliency. Then a more robust saliency map is obtained. It has been tested on many images to evaluate the validity and effectiveness of the proposed method. We also compare our method with other salient region detection methods and our method outperforms other methods in detection results.