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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08 Jul 2014
TL;DR: This paper was aimed to discuss and analyze about various image enhancement techniques and filters that are used to enhance the quality of the given input image.
Abstract: From the very beginning of the concept of image processing, the researchers took the challenge of image enhancement process as an important focus since enhancing an image would result in improvement in the image quality. Image has to be enhanced prior to any mentioned processing. An optimal Enhancement technique should enhance both high quality and low quality images, and should highlight even small details hidden in the image. Infrared image enhancement refines the details immerged in the background and provide a noise free image as output. This paper was aimed to discuss and analyze about various image enhancement techniques and filters that are used to enhance the quality of the given input image.
14 citations
30 Oct 2009
TL;DR: The proposed algorithm could not only keep edge information of an image, but also could improve signal-to-noise ratio of the denoised image.
Abstract: Edge information is the most important high- frequency information of an image, so we should try to maintain more edge information while denoising. In order to preserve image details as well as canceling image noise, we present a new image denoising method: image denoising based on edge detection. Before denoising, image's edges are first detected, and then the noised image is divided into two parts: edge part and smooth part. We can therefore set high denoising threshold to smooth part of the image and low denoising threshold to edge part. The theoretical analyses and experimental results presented in this paper show that, compared to commonly-used wavelet threshold denoising methods, the proposed algorithm could not only keep edge information of an image, but also could improve signal-to-noise ratio of the denoised image.
14 citations
TL;DR: The aim is to produce a transformation of the spectrogram in which the instantaneous frequency lines are easier to track, for using it as an input for a (wolves howls) counting algorithm.
14 citations
TL;DR: In this paper, partial differential equations are applied to the image produced by time-frequency representations of one-dimensional signals, such as the spectrogram, for noise smoothing and edge enhancement.
14 citations
Patent•
30 Dec 2013TL;DR: In this article, the authors describe a differential phase contrast imaging system and methods for the same, which can provide regularized phase contrast retrieval that can address noise reduction and/or edge enhancement, and suppress stripe artifacts occurring in the process of integration of noisy differential phase data.
Abstract: Embodiments of methods and apparatus are disclosed for obtaining differential phase contrast imaging system and methods for same. Method and apparatus embodiments can provide regularized phase contrast retrieval that can address noise reduction and/or edge enhancement. Certain exemplary embodiments can suppress stripe artifacts occurring in the process of integration of noisy differential phase data. Further, certain exemplary embodiments can use transmission images and/or dark-field images to improve or restore phase contrast images affected by noise edges.
14 citations