scholarly journals Fuzzy Logic based Improvement in Discrete Wavelet Transform Edge Representation in Images.doc

2020 ◽  
Author(s):  
Anand Swaminathan
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Fuzzy Inference ◽  
Directional Derivative ◽  
Rule Base ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Wavelet Coefficients ◽  
Inference System ◽  
Rule Structure

We introduce a rule base fuzzy technique on decomposed wavelet coefficients, to improve the wavelet edge representation. Our algorithm mitigates ‘incorrect’ responses, due primarily to the symmetries of directional derivative filters. Since the Discrete Wavelet Transform (DWT) coefficients are revealed from two dimensional symmetric filter banks and undermine some gradient information. These wavelet coefficients are prearranged into ‘if-then’ rule structure of a fuzzy inference system, to improve the wavelet edge representation.

scholarly journals Fuzzy Logic based Improvement in Discrete Wavelet Transform Edge Representation in Images.doc

2020 ◽  
Author(s):  
Anand Swaminathan
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Fuzzy Inference ◽  
Directional Derivative ◽  
Rule Base ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Wavelet Coefficients ◽  
Inference System ◽  
Rule Structure

We introduce a rule base fuzzy technique on decomposed wavelet coefficients, to improve the wavelet edge representation. Our algorithm mitigates ‘incorrect’ responses, due primarily to the symmetries of directional derivative filters. Since the Discrete Wavelet Transform (DWT) coefficients are revealed from two dimensional symmetric filter banks and undermine some gradient information. These wavelet coefficients are prearranged into ‘if-then’ rule structure of a fuzzy inference system, to improve the wavelet edge representation.

scholarly journals The Improvement of Discrete Wavelet Transform

2021 ◽  
Author(s):  
Zhihua Zhang
Keyword(s):  
Wavelet Transform ◽  
Decay Rate ◽  
Discrete Wavelet Transform ◽  
Wavelet Transforms ◽  
Polynomial Interpolation ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Wavelet Coefficients ◽  
Periodic Wavelet ◽  
Improved Algorithm

Discrete wavelet transform and discrete periodic wavelet transform have been widely used in image compression and data approximation. Due to discontinuity on the boundary of original data, the decay rate of the obtained wavelet coefficients is slow. In this study, we use the combination of polynomial interpolation and one-dimensional/two-dimensional discrete periodic wavelet transforms to mitigate boundary effects. The decay rate of the obtained wavelet coefficients in our improved algorithm is faster than that of traditional two-dimensional discrete wavelet transform. Moreover, our improved algorithm can be extended naturally to the higher-dimensional case.

scholarly journals High Impedance Fault Detection in MV Distribution Network using Discrete Wavelet Transform and Adaptive Neuro-Fuzzy Inference System

2018 ◽  
Author(s):  
Veerapandiyan Veerasamy ◽  
Noor Izzri Abdul Wahab ◽  
Rajeswari Ramachandran ◽  
Muhammad Mansoor ◽  
Mariammal Thirumeni
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Discrete Wavelet ◽  
Inference System ◽  
High Impedance ◽  
Neuro Fuzzy ◽  
High Impedance Fault ◽  
Anfis Classifier

This paper presents a method to detect and classify the high impedance fault that occur in the medium voltage distribution network using discrete wavelet transform (DWT) and adaptive neuro-fuzzy inference system (ANFIS). The network is designed using Matlab software and various faults such as high impedance, symmetrical and unsymmetrical fault have been applied to study the effectiveness of the proposed ANFIS classifier method. This is achieved by training the ANFIS classifier using the features (standard deviation values) extracted from the three phase fault current signal by DWT technique for various cases of fault with different values of fault resistance in the system. The success and discrimination rate obtained for identifying and classifying the high impedance fault from the proffered method is 100% whereas the values are 66.7% and 85% respectively for conventional fuzzy based approach. The results indicate that the proposed method is more efficient to identify and discriminate the high impedance fault accurately from other power system faults in the system.

scholarly journals Discrete Wavelet Transform with Adaptive Network-Based Fuzzy Inference System for Compression of Images

2019 ◽  
Vol 8 (9) ◽  
pp. 748-756
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Image Encryption ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Median Filter ◽  
Discrete Wavelet ◽  
Hybrid Technique ◽  
Adaptive Network ◽  
Inference System

Image Encryption has a significant role to play in different fields like information security.Images are encryptedfor various purposes. Compression refers to the process that is carried out once the encryption is completed. In this review work, a hybrid technique has been followed for image encryption and decryption. First, input images are sent for preprocessing employing the median filter with the aim of removing the noise that is regarded to be unnecessary. This elimination process aids in improving the quality of the particular image. So the denoised image can be divided into different segments with the goal of encrypting the various blocks of images. This way, the required and unwanted blocks can be found during this above mentioned process. Encryption technique would follow Hybrid Chaos along with Discrete Cosine Transform shortly known as DCT. The encrypted image is then compressed with the help of Discrete Wavelet Transform (DWT) With Adaptive Network-Based Fuzzy Inference System (ANFIS). The experimental results indicate that the newly introduced DWT-ANFIS based compression attains a better performance in comparison with the availablecompression approaches in terms of Compression Ratio (CR) and Peak-Signal-Noise-Ratio (PSNR)

Sign in / Sign up

Export Citation Format

Share Document