scholarly journals Quaternion matrix singular value decomposition and its applications for color image processing

2004 ◽  
Author(s):  
Soo-ChangPei ◽  
Ja-Han Chang ◽  
Jian-Jiun Ding
Keyword(s):  
Image Processing ◽  
Singular Value Decomposition ◽  
Color Image ◽  
Singular Value ◽  
Color Image Processing ◽  
Quaternion Matrix ◽  
Value Decomposition

scholarly journals Pengenalan Gangguan Ginjal Melalui Iridologi Menggunakan Hidden Markov Model (HMM)

2019 ◽  
Vol 9 (2) ◽  
pp. 19-26
Author(s):  
Reza Satria Rinaldi ◽  
Wagiasih Wagiasih ◽  
Ika Novia Anggraini
Keyword(s):  
Image Processing ◽  
Singular Value Decomposition ◽  
Markov Model ◽  
Hidden Markov Model ◽  
Hidden Markov ◽  
Singular Value ◽  
Parameter Determination ◽  
Iris Image ◽  
Determination System ◽  
Value Decomposition

ABSTRACTIridology has not been widely applied for the recognition of kidney disorders. identification of kidney disorders through iris image using iridology chart, can make it easier to make diagnosis to find out about kidney disorders. The method used in the process of recognition of kidney disorders through iridology is the Hidden Markov Model (HMM) method, with a HMM parameter determination system using the calculation of the koefisien Singular Value Decomposition (SVD) coefficient. The size of the codebook used is 7, i.e. 16, 32, 64, 128, 256, 512 and 1024. Different sizes of codebooks will result in different recognition times. The time needed will be longer when the size of the codebook is getting bigger. The accuracy of the process of recognition of kidney disorders through iridology using the HMM method in this study is 68.75% for codebook 16, 87.5% for codebook 32, 100% for codebook 128 and 100% for codebook 512. Keywords : iridology, codebook, image processing, singular value decomposition (SVD), Hidden Markov Model (HMM).

A robust color image watermarking with Singular Value Decomposition method

2011 ◽  
Vol 42 (6) ◽  
pp. 336-346 ◽  
Author(s):  
Sengul Dogan ◽  
Turker Tuncer ◽  
Engin Avci ◽  
Arif Gulten
Keyword(s):  
Singular Value Decomposition ◽  
Decomposition Method ◽  
Color Image ◽  
Image Watermarking ◽  
Singular Value ◽  
Color Image Watermarking ◽  
Singular Value Decomposition Method ◽  
Value Decomposition

scholarly journals Image fusion algorithm based on improved K-singular value decomposition and Hadamard measurement matrix

2018 ◽  
Vol 13 ◽  
pp. 174830181879151
Author(s):  
Qiang Yang ◽  
Huajun Wang
Keyword(s):  
Singular Value Decomposition ◽  
Image Fusion ◽  
Compressive Sensing ◽  
Color Image ◽  
Singular Value ◽  
Measurement Matrix ◽  
Fusion Algorithm ◽  
Full Color ◽  
Value Decomposition ◽  
Time And Space Complexity

To solve the problem of high time and space complexity of traditional image fusion algorithms, this paper elaborates the framework of image fusion algorithm based on compressive sensing theory. A new image fusion algorithm based on improved K-singular value decomposition and Hadamard measurement matrix is proposed. This proposed algorithm only acts on a small amount of measurement data after compressive sensing sampling, which greatly reduces the number of pixels involved in the fusion and improves the time and space complexity of fusion. In the fusion experiments of full-color image with multispectral image, infrared image with visible light image, as well as multispectral image with full-color image, this proposed algorithm achieved good experimental results in the evaluation parameters of information entropy, standard deviation, average gradient, and mutual information.

Application Of Singular Value Decomposition To Digital Image Processing

1990 ◽  
Author(s):  
Methodi Kovatchev ◽  
Evgeni Mitev ◽  
Rumiana Nedkova ◽  
Methodi Kovatchev ◽  
Evgeni Mitev ◽  
...  
Keyword(s):  
Image Processing ◽  
Singular Value Decomposition ◽  
Digital Image Processing ◽  
Digital Image ◽  
Singular Value ◽  
Value Decomposition

Color Image Compression Using Block Singular Value Decomposition

2013 ◽  
Vol 303-306 ◽  
pp. 2122-2125
Author(s):  
Peng Fei Xu ◽  
Hong Bin Zhang ◽  
Xin Feng Wang ◽  
Zheng Yong Yu
Keyword(s):  
Singular Value Decomposition ◽  
Image Compression ◽  
Basic Principle ◽  
Color Image ◽  
Singular Value ◽  
Matrix Structure ◽  
Compression Scheme ◽  
The Matrix ◽  
Value Decomposition ◽  
Color Image Compression

This paper looks at the application of Singular Value Decomposition (SVD) to color image compression. Based on the basic principle and characteristics of SVD, combined with the image of the matrix structure. A block SVD-based image compression scheme is demonstrated and the usage feasibility of Block SVD-based image compression is proved.

Jacobi method for quaternion matrix singular value decomposition

2007 ◽  
Vol 187 (2) ◽  
pp. 1265-1271 ◽  
Author(s):  
Nicolas Le Bihan ◽  
Stephen J. Sangwine
Keyword(s):  
Singular Value Decomposition ◽  
Singular Value ◽  
Jacobi Method ◽  
Quaternion Matrix ◽  
Value Decomposition

Assessment of color image fusion algorithms based on quaternion singular value decomposition

2009 ◽  
Author(s):  
Yuqing Wang ◽  
Ming Zhu ◽  
Haochen Pang ◽  
Yong Wang
Keyword(s):  
Singular Value Decomposition ◽  
Image Fusion ◽  
Color Image ◽  
Singular Value ◽  
Value Decomposition
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