MATLAB Implementation of "Context-Aware Saliency Detection" Paper

Paper Content: The Context-Aware Saliency Detection algorithm proposed in this paper represents a saliency detection method based on image contextual information. Unlike traditional algorithms that only consider local contrast, this approach captures the global layout of scenes through multi-scale analysis, thereby more accurately identifying regions that attract human visual attention.

The core algorithm framework consists of three key steps: First, analyzing feature distributions of image regions at different scales; Second, calculating preliminary saliency maps using the center-surround difference principle; Finally, generating the final saliency detection output by integrating results from multiple scales. The innovation lies in emphasizing the influence of scene context on saliency judgment, making detection results more consistent with human visual perception patterns.

In the MATLAB implementation, the algorithm primarily utilizes color features and positional information as computational foundations. The implementation involves techniques such as image pyramid construction, feature distance calculation, and multi-scale result fusion. The code structure clearly modularizes the entire workflow, facilitating comprehension and modification. Notably, this method is particularly suitable for handling saliency detection tasks in complex scenarios, such as natural images and street view environments.