The things that deserve our attention in an image are not the image patches that follow the 1/f law, but the patches that stick out of the smooth curves, in other words, statistical anomalies. These anomalies are termed the spectral residual of an image and correspond to the potentially interesting patches of an image (or proto-objects). A map that shows these statistical anomalies as bright spots is called a saliency map.
The spectral residual approach described here is based on the original scientific publication article Saliency Detection: A Spectral Residual Approach by Xiaodi Hou and Liqing Zhang (2007), IEEE Transactions on Computer Vision and Pattern Recognition (CVPR), ...
