Sensor sharpening [J. Opt. Soc. Am. A 11, 1553 (1994)] has been proposed as a method for improving computational color constancy, but it has not been thoroughly tested in practice with existing color constancy algorithms. In this paper we study sensor sharpening in the context of viable color constancy processing, both theoretically and empirically, and on four different cameras. Our experiment...

Spectral sharpening is a method for developing camera or other optical-device sensor functions that are more narrowband than those in hardware, by means of a linear transform of sensor functions. The utility of such a transform is that many computer vision and color-correction algorithms perform better in a sharpened space, and thus such a space can be used as an intermediate representation for...

Pan-sharpening is the process of fusing a low resolution multispectral image with a high resolution panchromatic image to obtain a high resolution multispectral image. We propose a new pan-sharpening method called Variational Wavelet Pan-sharpening (VWP) that combines wavelet fusion and the edges of the panchromatic image as an energy minimization problem. Furthermore, we introduce additional e...

This article describes a method for clarifying and sharpening radiographs. The method uses convolution with a computed tomography reconstruction kernel and a noise elimination procedure to control the noise amplification of the convolution. The effect is to flatten global variations and to sharpen and magnify local variations. Examples from industry and medicine are included.

It is well-known that the mean squared error (MSE) is an inappropriate measure for the difference between two images in many applications. For one such an application, edge-preserving smoothing, an alternative was developed which takes both goals into account: the preservation or sharpening of edges and the smoothing of regions. In this paper, tests on human subjects are reported which con rm t...

Based on compressive sensing framework and sparse reconstruction technology, a new pan-sharpening method, named Sparse Fusion of Images (SparseFI, pronounced as sparsify), is proposed in [1]. In this paper, the proposed SparseFI algorithm is validated using UltraCam and WorldView-2 data. Visual and statistic analysis show superior performance of SparseFI compared to the existing conventional pa...

In this study, a sharpening method based on a neural network (NN) approximation technique is described to increase the spatial resolution of thematic mapper (TM) thermal-infrared (T-IR) data. Sharpening is derived from a learned input-output mapping of edge contrast patterns between TIR and higher resolution TM bands. This method is similar to a reported adaptive least squares (LS) method to es...

It is well-known that the mean squared error (MSE) is an inappropriate measure for the di erence between two images in many applications. For one such an application, edge-preserving smoothing, an alternative was developed which takes both goals into account: the preservation or sharpening of edges and the smoothing of regions. In this paper, tests on human subjects are reported which con rm th...

A new approach to sharpening blurred pictures using the moment-preserving principle is proposed. The new gray value assigned to each pixel in the desired picture is computed deterministically in such a way that the moments of the n x n neighborhood of the pixel are preserved. The selection of the neighborhood size n depends on the blurring degree of the picture. The sharpening operation can als...

Conventional sharpened cascaded-integrator-comb (CIC) filters use generic sharpening polynomials to improve the frequency response. In contrast to the existing literature, an optimization framework is described for the selection of CIC sharpening polynomial and an efficient implementation through Saramäki-Ritoniemi decimation structure is suggested for its realization. The optimized sharpening ...