Design of Natural Image Denoising Filter Based on Second-Generation Wavelet Transformation and Principle Component Analysis

2015 ◽  
Vol 5 (6) ◽  
pp. 1261-1266 ◽  
Author(s):  
Asem Khmag ◽  
Abd Rahman Ramli ◽  
S. A. R. Al-Haddad ◽  
S. J. Hashim ◽  
Zarina Mohd Noh ◽  
...  
Keyword(s):  
Image Denoising ◽  
Principle Component Analysis ◽  
Wavelet Transformation ◽  
Second Generation ◽  
Component Analysis ◽  
Natural Image ◽  
Principle Component ◽  
Second Generation Wavelet

scholarly journals Nonlocal Mean Image Denoising Using Anisotropic Structure Tensor

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Xi Wu ◽  
Mingyuan Xie ◽  
Wei Wu ◽  
Jiliu Zhou
Keyword(s):  
Image Denoising ◽  
Principle Component Analysis ◽  
Riemannian Space ◽  
Component Analysis ◽  
Structure Tensor ◽  
Anisotropic Structure ◽  
Principle Component ◽  
Boundary Information ◽  
Image Details

We present a novel nonlocal mean (NLM) algorithm using an anisotropic structure tensor to achieve higher accuracy of imaging denoising and better preservation of fine image details. Instead of using the intensity to identify the pixel, the proposed algorithm uses the structure tensor to characterize the boundary information around the pixel more comprehensively. Meanwhile, similarity of the structure tensor is computed in a Riemannian space for more rigorous comparison, and the similarity weight of the pixel (or patch) is determined by the intensity and structure tensor simultaneously. The proposed algorithm is compared with the original NLM algorithm and a modified NLM algorithm that is based on the principle component analysis. Quantitative and qualitative comparisons of the three NLM algorithms are presented as well.

ANALYSIS OF VOICE CUES IN RECOGNITION OF SARCASM

2019 ◽  
Vol 12 ◽  
Author(s):  
Basavaraj N Hiremath ◽  
Malini M Patilb
Keyword(s):  
Feature Extraction ◽  
Computer Program ◽  
Principle Component Analysis ◽  
Voice Recognition ◽  
Component Analysis ◽  
Recognition System ◽  
Principle Component ◽  
Whole Process ◽  
The Voice

The voice recognition system is about cognizing the signals, by feature extraction and identification of related parameters. The whole process is referred to as voice analytics. The paper aims at analysing and synthesizing the phonetics of voice using a computer program called “PRAAT”. The work carried out in the paper also supports the analysis of voice segmentation labelling, analyse the unique features of voice cues, understanding physics of voice, further the process is carried out to recognize sarcasm. Different unique features identified in the work are, intensity, pitch, formants related to read, speak, interactive and declarative sentences by using principle component analysis.

Four challenges for cognitive neuroscience and the cortico-hippocampal division of memory

2003 ◽  
Vol 26 (6) ◽  
pp. 681-682
Author(s):  
Harry Howard
Keyword(s):  
Independent Component Analysis ◽  
Recent Work ◽  
Cognitive Neuroscience ◽  
Principle Component Analysis ◽  
Pattern Analysis ◽  
Component Analysis ◽  
Independent Component ◽  
Principle Component ◽  
Complementary Methods ◽  
Current State

Jackendoff's criticisms of the current state of theorization in cognitive neuroscience are defused by recent work on the computational complementarity of the hippocampus and neocortex. Such considerations lead to a grounding of Jackendoff's processing model in the complementary methods of pattern analysis effected by independent component analysis (ICA) and principle component analysis (PCA).

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