Static Image Saliency Analysis Toolbox

This paper presents a MATLAB-based static image saliency analysis program designed to help computer vision researchers and practitioners identify the most visually prominent elements in images. The implementation incorporates advanced algorithms including XXX, YYY, and ZZZ - widely adopted techniques in computer vision that demonstrated exceptional performance in our experiments. The algorithmic framework processes input images through multi-scale feature extraction, contrast computation, and spatial weighting mechanisms to generate saliency maps. Key MATLAB functions include feature normalization routines, Gaussian pyramid decomposition, and center-surround difference calculations. Our research benefited from guidance and support by three renowned Caltech professors whose expertise in computer vision significantly influenced our methodology. We believe this work provides valuable insights for computer vision professionals, offering both practical implementation tools and theoretical understanding of visual attention mechanisms.