Multi‐scale contrast‐based saliency enhancement for salient object detection

Abstract

To achieve more complete and more uniformly highlighted salient object regions, this study presents a computational saliency enhancement model that incorporates the properties of multi‐scale and logarithmic response into the local and global contrasts. A distinct feature of the authors model is a novel saliency enhancement operator. This operator can effectively enhance the saliency of object interior regions while simultaneously reducing blur on object boundaries caused by multiple scales. Their model is a general one that can make flexible tradeoffs between precision and recall. Detailed comparisons with 12 state‐of‐the‐art methods show that their method can obtain satisfactory salient object regions that are closer to the human‐labelled results. In addition, their method provides superior results in precision–recall, F‐measure and mean absolute error.

Keywords

• multiscale contrast-based saliency enhancement operator
• salient object detection
• computational saliency enhancement model
• logarithmic response property
• object interior region
• blur reduction