Topic
Edge enhancement
About: Edge enhancement is a research topic. Over the lifetime, 2324 publications have been published within this topic receiving 30962 citations.
Papers published on a yearly basis
Papers
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TL;DR: In this paper, a phase mismatched spiral phase plate (SPP) fabricated by electron beam lithography is employed as the radial Hilbert transform for image edge enhancement, which is simple, economical, reliable, and easy to integrate.
Abstract: We present a spiral phase filtering system with a large tolerance for edge enhancement of both phase and amplitude objects in optical microscopy. The method is based on a Fourier 4-f spatial filtering system. A phase mismatched spiral phase plate (SPP) fabricated by electron beam lithography is employed as the radial Hilbert transform for image edge enhancement. Compared with holography, SPP is simple, economical, reliable, and easy to integrate.
6 citations
TL;DR: A snake-based segmentation method of extracting the target from the reference window based on the joint transform architecture, including a holographic edge enhancement filter and a “snake”-based optical segmentation was constructed and tested successfully.
6 citations
06 Mar 2008
TL;DR: Preliminary results show that computer-aided detection of tubes in portable chest X-ray images is promising and it is expected that automated detection of ET tubes could lead to timely detection of malpositioned tubes, thus improve overall patient care.
Abstract: In intensive care units (ICU), endotracheal (ET) tubes are inserted to assist patients who may have difficulty breathing.
A malpositioned ET tube could lead to a collapsed lung, which is life threatening. The purpose of this study is to
develop a new method that automatically detects the positioning of ET tubes on portable chest X-ray images. The
method determines a region of interest (ROI) in the image and processes the raw image to provide edge enhancement for
further analysis. The search of ET tubes is performed within the ROI. The ROI is determined based upon the analysis of
the positions of the detected lung area and the spine in the image. Two feature images are generated: a Haar-like image
and an edge image. The Haar-like image is generated by applying a Haar-like template to the raw ROI or the enhanced
version of the raw ROI. The edge image is generated by applying a direction-specific edge detector. Both templates are
designed to represent the characteristics of the ET tubes. Thresholds are applied to the Haar-like image and the edge
image to detect initial tube candidates. Region growing, combined with curve fitting of the initial detected candidates, is
performed to detect the entire ET tube. The region growing or "tube growing" is guided by the fitted curve of the initial
candidates. Merging of the detected tubes after tube growing is performed to combine the detected broken tubes. Tubes
within a predefined space can be merged if they meet a set of criteria. Features, such as width, length of the detected
tubes, tube positions relative to the lung and spine, and the statistics from the analysis of the detected tube lines, are
extracted to remove the false-positive detections in the images. The method is trained and evaluated on two different
databases. Preliminary results show that computer-aided detection of tubes in portable chest X-ray images is promising.
It is expected that automated detection of ET tubes could lead to timely detection of malpositioned tubes, thus improve
overall patient care.
6 citations
01 Jan 2005
TL;DR: Using local coordinate transform, the first and second order normal derivatives of edge and local detail and the hyperbolic tangent function, also combining the anisotropic diffusion equation, Wang et al. as mentioned in this paper put forth an ultrasonic image denoising and edge enhancement scheme, which can preserve edges, local details and ultrasonic echoic bright strips.
Abstract: Utilizing the echoic intension and distribution of different organizations and local details,ultrasonic image catches the important medical pathological changes.However ultrasonic image may be contaminated by the speckle noise in its forming process,which degrades image quality specially concealing some details,and works disadvantages to image segmentation,character extraction and image recognition,disease diagnosis and quantitative analysis.Using local coordinate transform,the first and second order normal derivatives of edge and local detail and the hyperbolic tangent function,also combining the anisotropic diffusion equation,we have put forth an ultrasonic image denoising and edge enhancement scheme,which can preserve edges,local details and ultrasonic echoic bright strips on denoising.This has been indicated theoretically and experimentally.
6 citations
Patent•
06 Oct 2003
TL;DR: In this article, the authors propose an X-ray radiographic apparatus capable of performing frequency processing, e.g. smoothing (noise removal) and sharpening (edge enhancement), appropriately depending on the distribution of resolution occurring in the photographing region of a photographing means.
Abstract: PROBLEM TO BE SOLVED: To provide a X-ray radiographic apparatus capable of performing frequency processing, e.g. smoothing (noise removal) and sharpening (edge enhancement), appropriately depending on the distribution of resolution occurring in the photographing region of a photographing means due to bubbles in the production process and ensuring good diagnostic power. SOLUTION: The X-ray radiographic apparatus comprises a photographing means outputting radiographic image data of an object, a first memory for storing the image data from the photographing means, a means for detecting resolution distribution of the photographing means, a second memory for storing the resolution distribution detected by the resolution detecting means, and an image processing means performing frequency processing of the image data stored in the first memory at an intensity dependent on the resolution distribution stored in the second memory. COPYRIGHT: (C)2005,JPO&NCIPI
6 citations