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3 articles for “wavelet edge detection”
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Edge Preserving Image De-noising using Adaptive Thresholding
Abstract: This paper proposes a new image denoising method that is the wavelet threshold denoising of image based on edge detection. Before denoising, wavelet coefficients of an image are first detected, that correspond to edges. Then, the detected coefficients i.e. edges will be preserved from denoising by reducing the threshold coefficient of the original threshold then apply the reduced threshold and this will further protect edges from any damage. In this …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 3, 2015 · pp. 20–29 Read article
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Brief Review of Medical Image Fusion Techniques Based on Hybrid Intelligence
Abstract: An image fusion combines complementary images from multiple images such that the fused image is more suitable for further processing tasks or specific application. The goal of image fusion is to integrate complementary multi sensor, multi temporal and/or multi view data into a new image containing more information for proper medical diagnosis and different application tasks. The purpose of this paper is a survey of image fusion algorithms based on …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 1, 2016 · pp. 8–15 Read article
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Detect the Edges of Hygienic Images and De-Noised Images Using Meta Heuristic and F-Ratio
Abstract: AbstractEdge detection is one of the important parts of image processing. It is essentially involved in the pre-processing stage of image analysis and computer vision. It generally detects the contour of an image and thus provides important details about an image. So, it reduces the content to process for the high-level processing tasks like object recognition and image segmentation. The most important step in the edge detection, on which the …
Published in Journal of Advances in Shell Programming · Vol. 4, Issue 2, 2017 · pp. 19–25 Read article