Directional selection of 2D complex discrete wavelet transform and its application to image processing

2008 ◽  
Author(s):  
Zhong Zhang ◽  
Nariya Komazaki ◽  
Hiroshi Toda ◽  
Tetsuo Miyake ◽  
Takashi Imamura
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Directional Selection ◽  
Discrete Wavelet ◽  
Selection Of

DIRECTIONAL SELECTION OF TWO-DIMENSIONAL COMPLEX DISCRETE WAVELET TRANSFORM AND ITS APPLICATION TO IMAGE PROCESSING

2010 ◽  
Vol 08 (04) ◽  
pp. 659-676 ◽  
Author(s):  
ZHONG ZHANG ◽  
NARIYA KOMAZAKI ◽  
TAKASHI IMAMURA ◽  
TETSUO MIYAKE ◽  
HIROSHI TODA
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Directional Selection ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Directional Filter ◽  
Sampling Process ◽  
Frequency Components ◽  
Selection Of

In this study, a novel direction selection method using the two-dimensional complex discrete wavelet transform (2D-CDWT) is proposed. In order to achieve arbitrary direction selection, the directional filters are first designed. Calculation procedure of directional selection can be shown as follows: (1) The 16 sub-images are generally generated from the original image by the 2D-CDWT without a down-sampling process and the 12 sub-images that correspond to the high-frequency components are selected. (2) The 12 sub-images are filtered by using the designed directional filter. (3) The down-sampling process is carried out and the resulting images are obtained. Furthermore, this method is applied to the surface analysis of a wafer, and it is confirmed that our method is effective in detecting irregular direction components.

SOME NOTES ON THE APPLICATION OF DISCRETE WAVELET TRANSFORM IN IMAGE PROCESSING

2011 ◽  
Author(s):  
Egydio C. S. Caria ◽  
Trajano A. de A. Costa ◽  
João Marcos A. Rebello ◽  
Donald O. Thompson ◽  
Dale E. Chimenti
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet

scholarly journals HOUGH TRANSFORM GENERATED STRONG IMAGE HASHING SCHEME FOR COPY DETECTION

2018 ◽  
Author(s):  
Mayank Srivastava ◽  
Jamshed M Siddiqui ◽  
Mohammad Athar Ali
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Hough Transform ◽  
Rapid Development ◽  
Discrimination Performance ◽  
Discrete Wavelet ◽  
Image Hashing ◽  
Copy Detection ◽  
Detection Scheme

The rapid development of image editing software has resulted in widespread unauthorized duplication of original images. This has given rise to the need to develop robust image hashing technique which can easily identify duplicate copies of the original images apart from differentiating it from different images. In this paper, we have proposed an image hashing technique based on discrete wavelet transform and Hough transform, which is robust to large number of image processing attacks including shifting and shearing. The input image is initially pre-processed to remove any kind of minor effects. Discrete wavelet transform is then applied to the pre-processed image to produce different wavelet coefficients from which different edges are detected by using a canny edge detector. Hough transform is finally applied to the edge-detected image to generate an image hash which is used for image identification. Different experiments were conducted to show that the proposed hashing technique has better robustness and discrimination performance as compared to the state-of-the-art techniques. Normalized average mean value difference is also calculated to show the performance of the proposed technique towards various image processing attacks. The proposed copy detection scheme can perform copy detection over large databases and can be considered to be a prototype for developing online real-time copy detection system.   

A Content-Based Watermarking Scheme for Image Authentication Using Discrete Wavelet Transform Inter-Coefficient Relations

2011 ◽  
pp. 173-187
Author(s):  
Latha Parameswaran ◽  
K Anbumani
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Image Authentication ◽  
Binary String ◽  
Discrete Wavelet ◽  
Host Image ◽  
Relationship Of ◽  
Watermarking Scheme ◽  
Authentication Technique

This chapter discusses a content-based authentication technique based on inter-coefficient relationship of Discrete Wavelet Transform (DWT). Watermark is generated from the first level DWT. An image digest (which is a binary string) is generated from the second level DWT. The watermark is embedded in the mid-frequency coefficients of first level DWT as directed by the image digest. Image authentication is done by computing the Completeness of Signature. The proposed scheme is capable of withstanding incidental image processing operations such as compression and identifies any malicious tampering done on the host image.

scholarly journals Analysis of the Quantization Noise in Discrete Wavelet Transform Filters for Image Processing

Electronics ◽  
2018 ◽  
Vol 7 (8) ◽  
pp. 135 ◽  
Author(s):  
Nikolay Chervyakov ◽  
Pavel Lyakhov ◽  
Dmitry Kaplun ◽  
Denis Butusov ◽  
Nikolay Nagornov
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Integrated Circuit ◽  
Filter Banks ◽  
Signal To Noise Ratio ◽  
Quantization Noise ◽  
Discrete Wavelet ◽  
Field Programmable ◽  
Application Specific Integrated Circuit

In this paper, we analyze the noise quantization effects in coefficients of discrete wavelet transform (DWT) filter banks for image processing. We propose the implementation of the DWT method, making it possible to determine the effective bit-width of the filter banks coefficients at which the quantization noise does not significantly affect the image processing results according to the peak signal-to-noise ratio (PSNR). The dependence between the PSNR of the DWT image quality on the wavelet and the bit-width of the wavelet filter coefficients is analyzed. The formulas for determining the minimal bit-width of the filter coefficients at which the processed image achieves high quality (PSNR ≥ 40 dB) are given. The obtained theoretical results were confirmed through the simulation of DWT for a test image using the calculated bit-width values. All considered algorithms operate with fixed-point numbers, which simplifies their hardware implementation on modern devices: field-programmable gate array (FPGA), application-specific integrated circuit (ASIC), etc.

On-Line Seam Detection in Rolling Processes Using Snake Projection and Discrete Wavelet Transform

2007 ◽  
Vol 129 (5) ◽  
pp. 926-933 ◽  
Author(s):  
Jing Li ◽  
Jianjun Shi ◽  
Tzyy-Shuh Chang
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Projection Method ◽  
Discrete Wavelet ◽  
On Line ◽  
Feature Preserving ◽  
Two Parameters ◽  
T2 Control Chart ◽  
Speed And Accuracy ◽  
Selection Of

This paper describes the development of an on-line quality inspection algorithm for detecting the surface defect “seam” generated in rolling processes. A feature-preserving “snake-projection” method is proposed for dimension reduction by converting the suspicious seam-containing images to one-dimensional sequences. Discrete wavelet transform is then performed on the sequences for feature extraction. Finally, a T2 control chart is established based on the extracted features to distinguish real seams from false positives. The snake-projection method has two parameters that impact the effectiveness of the algorithm. Thus, selection of the parameters is discussed. Implementation of the proposed algorithm shows that it satisfies the speed and accuracy requirements for on-line seam detection.

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