Edge enhancement

About: Edge enhancement is a research topic. Over the lifetime, 2324 publications have been published within this topic receiving 30962 citations.

Spiral phase filtering and orientation-selective edge detection/enhancement

Abstract: A spiral phase plate with an azimuthal structure exp[iϕ](0⩽ϕ<2π) has been used as a filter in a 4f system to achieve edge enhancement. Generally such edge-enhanced effect is isotropic, i.e., each edge of an input pattern is enhanced to the same degree regardless of its orientation. We found that one can achieve anisotropic edge enhancement by breaking down the symmetry of the filtering process. This can be done in two ways: first, by use of a fractional spiral phase filter (SPF) with a fractional topological charge and a controllable orientation of the edge discontinuity, and second, by the lateral shifting of the SPF. We interpret this process as a vortex formation due to the diffraction of the Fourier spectrum of the input pattern by a SPF with an integer and fractional topological charge. Optical experiments using a spatial light modulator were carried out to verify our proposal.

Classifying color edges in video into shadow-geometry, highlight, or material transitions

Abstract: We aim at using color information to classify the physical nature of edges in video. To achieve physics-based edge classification, we first propose a novel approach to color edge detection by automatic noise-adaptive thresholding derived from sensor noise analysis. Then, we present a taxonomy on color edge types. As a result, a parameter-free edge classifier is obtained labeling color transitions into one of the following types: 1) shadow-geometry, 2) highlight edges, and 3) material edges. The proposed method is empirically verified on images showing complex real world scenes.

Phase contrast enhancement of x-ray mammography: a design study

Abstract: This paper explores the application to mammography of phase contrast produced by variations in x-ray refractive index. As a spatially coherent x-ray beam propagates through an x-ray transparent medium, the phase of the incident wavefront becomes modified in a manner related to the electron density of the medium. The resulting phase gradient across the wavefront is equivalent to a small change in direction of the propagation of the wave. For a general object, the change in propagation direction will vary from point to point depending on the structures within the object. The net effect can be recorded in a radiographic image using an appropriate geometry to produce the visual appearance of edge enhancement at interfaces between materials with differing x-ray refractive indices. Normally these materials will also have differences in attenuation coefficient, so the overall effect is to increase the visibility of interfaces between materials. It is proposed that mammographic images can be subtly enhanced by the use of phase contrast information to overcome some of the known limitations of the imaging process whilst leaving the gross radiological appearance of the images substantially unchanged. The design trade-offs required to utilize phase contrast information were investigated using a conventional mammographic x-ray generator and film-screen system. The Leeds TORMAM mammographic image quality test object was then used to demonstrate a considerable improvement in image quality for the phase contrast enhanced images over those produced in the conventional geometry with no increase in radiation dose to the patient. The results are discussed in terms of their possible practical application.

Radial Hilbert transform with Laguerre-Gaussian spatial filters

Abstract: We analyze the point spread function (PSF) of the image processing system for radial Hilbert transform and propose a novel spiral phase filter, called the Laguerre-Gaussian spatial filter (LGSF). Theoretical analysis and real experiments show that the LGSF possesses some advantages in comparison with the conventional spiral phase plate (SPP). For example, the PSF of the imaging system with a LGSF presents smaller suboscillations than that with the conventional SPP, which allows us to realize a radial Hilbert transform for achieving a high contrast edge enhancement with high resolution.

EEMEFN: Low-Light Image Enhancement via Edge-Enhanced Multi-Exposure Fusion Network

Abstract: This work focuses on the extremely low-light image enhancement, which aims to improve image brightness and reveal hidden information in darken areas. Recently, image enhancement approaches have yielded impressive progress. However, existing methods still suffer from three main problems: (1) low-light images usually are high-contrast. Existing methods may fail to recover images details in extremely dark or bright areas; (2) current methods cannot precisely correct the color of low-light images; (3) when the object edges are unclear, the pixel-wise loss may treat pixels of different objects equally and produce blurry images. In this paper, we propose a two-stage method called Edge-Enhanced Multi-Exposure Fusion Network (EEMEFN) to enhance extremely low-light images. In the first stage, we employ a multi-exposure fusion module to address the high contrast and color bias issues. We synthesize a set of images with different exposure time from a single image and construct an accurate normal-light image by combining well-exposed areas under different illumination conditions. Thus, it can produce realistic initial images with correct color from extremely noisy and low-light images. Secondly, we introduce an edge enhancement module to refine the initial images with the help of the edge information. Therefore, our method can reconstruct high-quality images with sharp edges when minimizing the pixel-wise loss. Experiments on the See-in-the-Dark dataset indicate that our EEMEFN approach achieves state-of-the-art performance.