Improvement of Image Transform Calculation Based on a Weighted Primitive

2006 ◽  
pp. 260-271
Author(s):  
María Teresa Signes Pont ◽  
Juan Manuel García Chamizo ◽  
Higinio Mora Mora ◽  
Gregorio de Miguel Casado
Keyword(s):  
Image Transform

A new class of biorthogonal wavelet systems for image transform coding

1998 ◽  
Vol 7 (7) ◽  
pp. 1000-1013 ◽  
Author(s):  
Dong Wei ◽  
Jun Tian ◽  
R.O. Wells ◽  
C.S. Burrus
Keyword(s):  
Transform Coding ◽  
Biorthogonal Wavelet ◽  
New Class ◽  
Image Transform

Dimension Reduction Using Image Transform for Content-Based Feature Extraction

2018 ◽  
pp. 26-40
Author(s):  
Sourav De ◽  
Madhumita Singha ◽  
Komal Kumari ◽  
Ritika Selot ◽  
Akshat Gupta
Keyword(s):  
Feature Extraction ◽  
Dimension Reduction ◽  
Image Feature ◽  
Extraction Technique ◽  
Image Transform ◽  
Improved Performance ◽  
Different Color ◽  
Feature Dimension ◽  
Feature Extraction Technique ◽  
Feature Dimension Reduction

Technological advancements in the field of machine learning have attempted classification of the images of gigantic datasets. Classification with content-based image feature extraction categorizes the images based on the image content in contrast to conventional text-based annotation. The chapter has presented a feature extraction technique based on application of image transform. The method has extracted meaningful features and facilitated feature dimension reduction. A technique, known as fractional coefficient of transforms, is adopted to facilitate feature dimension reduction. Two different color spaces, namely RGB and YUV, are considered to compare the classification metrics to figure out the best possible reduced feature dimension. Further, the results are compared to state-of-the-art techniques which have revealed improved performance for the proposed feature extraction technique.

An Image Transform Emphasizing Textural Features

1977 ◽  
pp. 178-197
Author(s):  
Alberto Apostolico ◽  
Sergio Vitulano
Keyword(s):  
Textural Features ◽  
Image Transform

Multi-focus image fusion based on L1 image transform

2020 ◽  
Author(s):  
Shuang Yu ◽  
Xiongfei Li ◽  
Mingrui Ma ◽  
Xiaoli Zhang ◽  
Shiping Chen
Keyword(s):  
Image Fusion ◽  
Focus Image ◽  
Image Transform

Image Denoising with Contour-Based Directionlet Transform

2014 ◽  
Vol 513-517 ◽  
pp. 3607-3611
Author(s):  
Huan An Xu ◽  
Guo Hua Peng ◽  
Zhe Liu
Keyword(s):  
Image Processing ◽  
Image Denoising ◽  
Numerical Experiments ◽  
Adaptive Threshold ◽  
Perceptual Quality ◽  
Laplacian Pyramid ◽  
Low Frequencies ◽  
Threshold Algorithm ◽  
Image Transform

A novel mutiscale and directionally adaptive image transform called contour based directionlet tansform is presented. Directionlet transform (DT) has shown its charming performance in image processing, but it has scrambled frequencies. Laplacian Pyramid is employed here to separate the low frequencies before applying DT for avoiding the drawback. And an adaptive threshold algorithm is proposed for denoising. Numerical experiments are performed to assess the applicability of the proposed method. The obtained results show that the proposed scheme outperforms Wavelet and Directionlet transforms in terms of numerical and perceptual quality.

Film Recording in the Image Transform System

SMPTE Journal ◽  
1978 ◽  
Vol 87 (2) ◽  
pp. 82-84 ◽  
Author(s):  
Pete Comandini ◽  
Toni Roth
Keyword(s):  
Image Transform
Sign in / Sign up

Export Citation Format

Share Document