Visual saliency for automatic target detection, boundary detection, and image quality assessment

Abstract

We present a visual saliency detection method and its applications. The proposed method does not require prior knowledge (learning) or any pre-processing step. Local visual descriptors which measure the likeness of a pixel to its surroundings are computed from an input image. Self-resemblance measured between local features results in a scalar map where each pixel indicates the statistical likelihood of saliency. Promising experimental results are illustrated for three applications: automatic target detection, boundary detection, and image quality assessment.