The goal of this paper is guided image filtering, which emphasizes the importance structure transfer during filtering by means an additional guidance image. Where classical filters structures using hand-designed functions, recent have been considerably advanced through parametric learning deep networks. state-of-the-art leverages networks to estimate two core coefficients filter. In work, we po...

In all-optical processors, enhancement of image details is the result of high-pass filtering. We describe an optoelectronic processor in which detail enhancement results from the digitally calculated difference between an original input image and its low-pass filtered version. The low-pass filtering is realized through the rank-order median and the morphological opening and closing operations c...

R Cromartie! and S M Pizerl,2 1 Department of Computer Science 2Departments of Radiology and Radiation Oncology The University of North Carolina at Chapel Hill Chapel Hill, N.C. 27599 Contrast enhancement is a fundamental step in the display of digital images. The end result of display is the perceived brightness occurring in the human observer; design of effective contrast enhancement mappings...

Traditional filtering methods operate on the entire signal or image. In some applications, however, errors are concentrated in specific regions or features. A prime example is images generated using computed tomography. Practical implementations limit the amount of high frequency content in the reconstructed image, and consequently, edges are blurred. We introduce a new post-reconstruction edge...

In this paper we propose a unified variational image editing model. It interprets image editing as a variational problem concerning the adaptive adjustments to the zeroand first-derivatives of the images which correspond to the color and gradient items. By varying the definition domain of each of the two items as well as applying diverse operators, the new model is capable of tackling a variety...

This paper introduces a method for accomplishing mammographic feature analysis by mul-tiresolution representations of the dyadic wavelet transform. Our approach consists of the application of non-linear enhancing functions E(z) within levels of a multiresolution representation. We show that there exists a simple constraint for E(z) such that image enhancement is guaranteed. Furthermore, a simpl...

Sharpening filters are used to highlight fine image details, including object edges. However, sharpening very specific different types of images as they may create undesired edge effects, over-highlight or emphasize noise. Laplacian, Laplacian Gaussian, high-boost, unsharp masking filters, and their extended algorithms among most widely spatial filters. This paper introduces a method that integ...