1. A method for improving iterative results of Content-Based Image Retrieval (CBIR) using relevance feedback, the method comprising: obtaining positive feedback images and negative feedback images via relevance feedback, the positive feedback images are those images deemed semantically relevant and the negative feedback images are those deemed semantically less relevant; within a feature space, moving positive candidate images towards the positive feedback images, the positive candidate images have similar low-level features as those of positive feedback images; within a feature space, distancing negative candidate images from the positive feedback images, the negative candidate images have similar low-level features as those of negative feedback images.