Edge enhancement

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

Image encoding and decoding method and apparatus using edge synthesis and inverse wavelet transform

Abstract: A digitized image is encoded by detecting edges in the image, encoding the position and sharpness of the detected edges, filtering the image by a low-pass filter to generate a low-frequency image, and encoding the low-frequency image. A digitized image encoded in this way is reconstructed by generating a horizontal edge image and a vertical edge image from the encoded edge position and sharpness information, synthesizing a pair of high-frequency images by filtering the horizontal and vertical edge images with an edge synthesis filter, decoding the low-frequency image, and performing an inverse wavelet transform on the decoded low-frequency image and the high-frequency images.

Application of digital image magnification for surface roughness evaluation using machine vision

Abstract: In this work, a machine vision system has been utilized to capture the images and then the quantification of the surface roughness of machined surfaces (ground, milled and shaped) is done by the application of regression analysis. Subsequently, original images have been magnified using Cubic Convolution interpolation technique and improved (edge enhancement) through Linear Edge Crispening algorithm. Based on the surface image features, a parameter called G a has been estimated using regression analysis, for the original images and for the magnified quality improved images. Finally, a comparison has been carried to establish correlation between magnification index, G a and surface roughness.

Single underwater image enhancement using depth estimation based on blurriness

Abstract: In this paper, we propose to use image blurriness to estimate the depth map for underwater image enhancement. It is based on the observation that objects farther from the camera are more blurry for underwater images. Adopting image blurriness with the image formation model (IFM), we can estimate the distance between scene points and the camera and thereby recover and enhance underwater images. Experimental results on enhancing such images in different lighting conditions demonstrate the proposed method performs better than other IFM-based enhancement methods.

Sidescatter x-ray detection system

Abstract: An edge enhancement X-ray imaging system inspects an object (10) for detecting an illegal component. The system illuminates the object (10) with penetrating radiation (11) which is sidescattered from the object (10) and captured by a pair of radiant detectors (14, 16). The detectors (14, 16) are symmetrically positioned opposite each other, being adjacent the two sides of the object (10). Each detector has a detecting surface substantially parallel to the beam for converting sidescattered radiation into a pair of electrical signals which define a location of an edge of the illegal component. In response to the electrical signals, a video display (20) produces a visual image of the edge. In another embodiment of the invention, the system further comprises a pair of backscatter detectors which convert the backscattered radiation into a second pair of electrical signals producing a second visual image on the video display (20). As a result of superimposing the second image onto the first image associated with the sidescatter detectors, the detection of components of the object is greatly improved.