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Books on the topic 'Thresholding'

Author: Grafiati

Published: 4 June 2021

Last updated: 4 May 2024

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1

Jeunmeure, L. F. C. Intelligent thresholding. Manchester: UMIST, 1995.

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2

Erickson, Stephen A. The (Coming) Age of Thresholding. Dordrecht: Springer Netherlands, 1999. http://dx.doi.org/10.1007/978-94-015-9271-0.

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3

Jansen, Maarten. Noise Reduction by Wavelet Thresholding. New York, NY: Springer New York, 2001. http://dx.doi.org/10.1007/978-1-4613-0145-5.

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4

Erickson, Stephen A. The (coming) age of thresholding. Dordrecht: Kluwer Academic Publishers, 1999.

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5

Bayat, Niloofar. Internet Subscription Plans: Thresholding, Throttling, and Zero-Rating. [New York, N.Y.?]: [publisher not identified], 2022.

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6

Thresholding. Dorrance Pub Co, 1997.

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7

Erickson, S. A. (Coming) Age of Thresholding. Springer London, Limited, 2013.

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8

Erickson, S. A. The Age of Thresholding. Springer, 2010.

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9

Erickson, S. A. The Age of Thresholding. Springer, 2012.

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10

Jansen, Maarten. Noise Reduction by Wavelet Thresholding. Springer London, Limited, 2012.

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11

Noise Reduction by Wavelet Thresholding. Springer, 2012.

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12

Noise Reduction by Wavelet Thresholding. Springer, 2001.

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13

Beginner's Guide to Multi-Level Image Thresholding. Taylor & Francis Group, 2020.

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14

Dey, Nilanjan, Nadaradjane Sri Madhava Raja, and Venkatesan Rajinikanth. Beginner's Guide to Multi-Level Image Thresholding. Taylor & Francis Group, 2020.

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15

Dey, Nilanjan, Nadaradjane Sri Madhava Raja, and Venkatesan Rajinikanth. Beginner's Guide to Multi-Level Image Thresholding. Taylor & Francis Group, 2020.

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16

Dey, Nilanjan, Nadaradjane Sri Madhava Raja, and Venkatesan Rajinikanth. Beginner's Guide to Multi-Level Image Thresholding. Taylor & Francis Group, 2020.

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17

Dey, Nilanjan, Nadaradjane Sri Madhava Raja, and Venkatesan Rajinikanth. Beginner's Guide to Multi-Level Image Thresholding. Taylor & Francis Group, 2020.

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18

Biswal, Narayan. Speaker Recognition Using Adaptive Thresholding: United States Patent 9972322. Independently Published, 2020.

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19

Sahandi, Mohammad Reza. Image compression using vector encoding: Illumination correction, noise reduction, and thresholding of digitized CCTV signals produce binary images which are encoded as vector lists---. Bradford, 1987.

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20

Rajakumar, P. S., S. Geetha, and T. V. Ananthan. Fundamentals of Image Processing. Jupiter Publications Consortium, 2023. http://dx.doi.org/10.47715/jpc.b.978-93-91303-80-8.

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Abstract:

"Fundamentals of Image Processing" offers a comprehensive exploration of image processing's pivotal techniques, tools, and applications. Beginning with an overview, the book systematically categorizes and explains the multifaceted steps and methodologies inherent to the digital processing of images. The text progresses from basic concepts like sampling and quantization to advanced techniques such as image restoration and feature extraction. Special emphasis is given to algorithms and models crucial to image enhancement, restoration, segmentation, and application. In the initial segments, the intricacies of digital imaging systems, pixel connectivity, color models, and file formats are dissected. Following this, image enhancement techniques, including spatial and frequency domain methods and histogram processing, are elaborated upon. The book then addresses image restoration, discussing degradation models, noise modeling, and blur, and offers insights into the compelling world of multi-resolution analysis with in-depth discussions on wavelets and image pyramids. Segmentation processes, especially edge operators, boundary detections, and thresholding techniques, are detailed in subsequent chapters. The text culminates by diving deep into the applications of image processing, exploring supervised and unsupervised learning, clustering algorithms, and various classifiers. Throughout the discourse, practical examples, real-world applications, and intuitive diagrams are integrated to facilitate an enriched learning experience. This book stands as an essential guide for both novices aiming to grasp the basics and experts looking to hone their knowledge in image processing. Keywords: Digital Imaging Systems, Image Enhancement, Image Restoration, Multi-resolution Analysis, Wavelets, Image Segmentation, Feature Extraction, SIFT, SURF, Image Classifiers, Supervised Learning, Clustering Algorithms.

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