Non-convex sparsity-inducing penalties outperform their convex counterparts, but generally sacrifice the cost function convexity. As a middle ground, we propose sharpening sparse regularizers (SSR) framework to design non-separable non-convex that induce sparsity more effectively than such as l <sub...

We present a new technique for sharpening compressed images in the discrete-cosine-transform domain. For images compressed using the JPEG standard, image sharpening is achieved by suitably scaling each element of the encoding quantization table to enhance the high-frequency characteristics of the image. The modified version of the encoding table is then transmitted in lieu of the original. Expe...

This paper explains the use of a sharpening filter to calculate the depth of an object from a blurred image of it. It presents a technique which is independent of edge orientation. The technique is based on the assumption that a defocused image of an object is the convolution of a sharp image of the same object with a two-dimensional Gaussian function whose spread parameter (SP) is related to t...

For high-speed low-complexity filter design, it is common practice to constrain the filters' coefficients to be power-oftwo or a sum of powers-of-two terms (P2), avoiding the full multiplication. Tapped interconnection of different sub-filters are sometimes used to enhance ripple and stop-band attenuation performances. An extension of the simple cascade architectures, suitable for hardware impl...

In this paper we present a sharpening operator for color images that is based on perceptual considerations about how human visual behaves for color scenes. Color contrast is an induction phenomenon of the visual system that varies the chromaticity of a color region depending on the color of its surround, provoking an enhanced perception of color scenes. This effect can be simulated by a sharpen...