Spatially-Varying Sharpness Map Estimation Based on the Quotient of Spectral Bands

Natural images suffer from defocus blur due to the presence of objects at different depths from the camera. Automatic estimation of spatially-varying sharpness has several applications including depth estimation, image quality assessment, information retrieval, image restoration among others. In this paper, we propose a sharpness metric based on the quotient of high- to low-frequency bands of the log-spectrum of the image gradients. Using the proposed sharpness metric, we obtain a descriptive dense sharpness map. We also propose a simple yet effective method to segment out-of-focus regions using a global threshold which is defined using weak textured regions present in the input image. Results over two publicly available databases show that the proposed method provides competitive performance when compared with state-of-the-art methods.