Single-Pixel Salient Object Detection via Discrete Cosine Spectrum Acquisition and Deep Learning

Single-pixel imaging (SPI) can reduce the cost and have the potential of being competent for some challenging tasks. However, for a SPI system, acquiring detailed information from a complex scene for complex vision task is a measurements-consuming process, by which low efficiency resulted is one of the important obstructions of SPI for practical application. Reasonable allocation of resources of measurements and calculations is one of the effective solutions to this problem. As a preprocessing procedure with a role of guidance, salient object detection can help the vision system focus more attention on the area with more important information to improve the efficiency. Therefore, in this letter, we explore the implement of salient object detection based on SPI system and present a scheme via discrete cosine spectrum (DCS) acquisition and deep learning model.