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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02 Dec 2001
TL;DR: More details of the overall system for subjective image enhancement, which is based on fusion of different algorithms, is provided and the test results for contrast and sharpness/smoothness as interesting image qualities are presented.
Abstract: In many image-processing applications the image quality should be improved to support the human perception. Image quality evaluation by human observers is, however, heavily subjective in nature. Individual observers judge the image quality differently. In many cases, the quality of the relevant part of image information, which is perceived by the observer, should reach a maximum. In previous works, an overall system for subjective image enhancement, which is based on fusion of different algorithms, was introduced. In this paper, more details of the overall-system structure are provided. Furthermore, the test results for contrast and sharpness/smoothness as interesting image qualities are also presented.
12 citations
09 Jul 2010
TL;DR: Nonsubsampled contourlet transform has better performance in representing image edges than separable wavelet for its anisotropy, directionality and shift-invariance, and is therefore well-suited for multi-scale edge enhancement.
Abstract: A method aimed at minimizing image noise while optimizing contrast of image subtle features based on nonsubsampled contourlet transform is presented in this paper. Nonsubsampled contourlet transform, which is a shift-invariant version of the contourlet transform, has better performance in representing image edges than separable wavelet for its anisotropy, directionality and shift-invariance, and is therefore well-suited for multi-scale edge enhancement. We modify the nonsubsampled contourlet coefficients of images in corresponding subbands via a new and operable nonlinear mapping function and take the noise into account for more precise reconstruction and better visualization. Experimental results on some medical images show that the proposed enhancement method effectively highlights subtle features while suppressing noise. A comparison with other enhancement algorithms, such as histogram equalization and contourlet-based enhancement approach, is also discussed.
12 citations
TL;DR: This paper discusses the pros and cons of color capture using standard color detectors and presents an alternative solution that does not rely on color filters at the camera, thus preserving the high lateral and vertical resolution of CSI instruments.
Abstract: Optical 3D profilers based on Coherence Scanning Interferometry (CSI) provide high-resolution non-contact metrology
for a broad range of applications. Capture of true color information together with 3D topography enables the detection of
defects, blemishes or discolorations that are not as easily identified in topography data alone. Uses for true color 3D
imaging include image segmentation, detection of dissimilar materials and edge enhancement. This paper discusses the
pros and cons of color capture using standard color detectors and presents an alternative solution that does not rely on
color filters at the camera, thus preserving the high lateral and vertical resolution of CSI instruments.
12 citations
21 Nov 2011
TL;DR: Two novel edge detection algorithms based on a negative alpha weighted quadratic filter based on the characteristics of the nonlinear filter are introduced, which operate on local regions and modify the color tones of uniform regions while preserving the original edges.
Abstract: In this paper, we introduce two novel edge detection algorithms based on a negative alpha weighted quadratic filter. The goal of this work is to utilize the characteristics of the nonlinear filter to preserve and enhance edges for the purpose of edge detection. Unlike traditional edge detection algorithms, which detect edges by using derivatives, the proposed algorithms operate on local regions and modify the color tones of uniform regions while preserving the original edges. We also incorporate the luminance mas2king feature of the Human Visual System by masking the gradient image before edge labeling. Experimental simulations show that the proposed algorithms can extract fine edge information from images contaminated by noise and affected by non-uniform illumination; the obtained edge maps are more consistent to the edges perceived by the human eye. Comparison with existing algorithms will be also presented.
12 citations
Patent•
01 Oct 1999
TL;DR: In this paper, each image frame is divided into non-overlapping blocks of pixels and each block is characterized by a value proportional to the contrast of the block, and if the block contrast is greater than a user-selectable contrast threshold, a window level operation is performed upon that pixel block.
Abstract: In a method and an apparatus for enhancing edges in computer-generated images, each image frame is divided into non-overlapping blocks of pixels Each block is characterized by a value proportional to the contrast of the block Each block is checked to see if its contrast is greater than a user-selectable contrast threshold If the block contrast is greater than the threshold, a window level operation is performed upon that pixel block This method restricts the window level edge enhancement function to just the set of pixel blocks that have a high contrast value and may contain an edge
12 citations