scholarly journals Fast Decomposition Algorithm Based on Two-Dimensional Wavelet Transform for Image Processing of Graphic Design

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Feifei Jiang ◽  
Wenting Yao
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Graphic Design ◽  
Low Frequency ◽  
Decomposition Algorithm ◽  
Feature Point ◽  
Two Dimensional ◽  
Feature Points ◽  
Long Time ◽  
Fast Decomposition

Graphic design is an important part of the design field today. In this era of information explosion, designs that can deliver information faster and more accurately are bound to gain popularity among the public. In this paper, we propose a fast decomposition algorithm image processing method based on a new transform of the wavelet transform, which mainly addresses the problems of large computation of feature points and long-time consumption of traditional image processing algorithms. Firstly, the second-order decomposition of the image is performed by wavelet function to obtain the low-frequency components of the image, and the wavelet gradient vector is used to extract feature points from the overlapping regions of the low-frequency image so that the transformation parameters of feature points can be obtained quickly under the low-frequency image to guide the feature point extraction under the high-frequency image; on this basis, an improved algorithm of image processing based on the fast decomposition algorithm of two-dimensional wavelet transform with planar design is proposed. Using the properties of one-way matching and directional consistency of feature point constraints, the mismatched point pairs are effectively eliminated to improve the feature point matching accuracy and real-time performance. Finally, the effectiveness and feasibility of the proposed method are verified by two sets of experiments.

Simultaneous Least Squares Wavelet Decomposition for Multidimensional Irregularly Spaced Data

2012 ◽  
Vol 239-240 ◽  
pp. 1213-1218 ◽  
Author(s):  
Mehdi Shahbazian ◽  
Saeed Shahbazian
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Wavelet Decomposition ◽  
Least Square ◽  
Multidimensional Case ◽  
Discrete Wavelet ◽  
Two Dimensional ◽  
Wavelet Coefficients ◽  
Sampled Data ◽  
Irregularly Sampled Data

The multidimensional Discrete Wavelet Transform (DWT) has been widely used in signal and image processing for regularly sampled data. For irregularly sampled data, however, other techniques should be used including the Least Square Wavelet Decomposition (LSWD). The commonly used level by level (sequential) wavelet decomposition, which calculates the wavelet coefficients in each resolution separately, may result in a gross interpolation error. To overcome this drawback, a different approach called the Simultaneous Least Square Wavelet Decomposition, which computes all wavelet coefficients simultaneously, have been proposed by the authors. In this paper, we extend the simultaneous LSWD approach to the multidimensional case and show that this method has excellent reconstruction property for two dimensional irregularly spaced data.

scholarly journals The Two-Dimensional Wavelet Transform De-noising and Combining with Side Scan Sonar Image

2017 ◽  
Vol 1 (01) ◽  
pp. 1-4 ◽  
Author(s):  
Muhammad Zainuddin Lubis ◽  
Rasyid Alkhoir Lubis ◽  
Ramadhan Ulil Albab Lubis
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Time Domain ◽  
Haar Wavelet ◽  
Quality Data ◽  
Two Dimensional ◽  
Unified Framework ◽  
Side Scan Sonar ◽  
Sonar Image ◽  
Time Domain Signal

This paper puts forward an image de-noising method based on 2D wavelet transform with the application of the method in seabed identification data collection system. Two-dimensional haar wavelets in image processing presents a unified framework for wavelet image compression and combining with side scan sonar image. Seabed identification target have 7 target detection in side scan sonar imagery result.  The vibration signals were analyzed to perform fault diagnosis. The obtained signal was time-domain signal. The experiment result shows that the application of 2D wavelet transform image de-noising algorithm can achieve good subjective and objective image quality and help to collect high quality data and analyze the images for the data center with optimum effects, the features from time-domain signal were extracted. 3 vectors were formed which are v1, v2, v3. In Haar wavelet retained energy is 93.8 %, so from the results, it has been concluded that Haar wavelet transform shows the best results in terms of Energy from De-noised Image processing with side scan sonar imagery.

A Kind of DWT Domain Image Digital Watermarking Algorithm Research

2014 ◽  
Vol 1044-1045 ◽  
pp. 991-994
Author(s):  
Tao Liu
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Frequency Domain ◽  
Digital Watermarking ◽  
Wavelet Decomposition ◽  
Low Frequency ◽  
Discrete Wavelet ◽  
Original Image ◽  
Adaptive Watermarking ◽  
Frequency Domain Methods

An image-adaptive watermarking algorithm based on wavelet transform was proposed. At first, A digital image used as watermarking was scrambled. Next, the original image was decomposed by discrete wavelet transform,and in accordance with the characteristics of human visual system, wavelet decomposition in the low-frequency domain, Methods which average of adjacent domain instead of single wavelet decomposition coefficients was used to estimate and quantitative, watermarking was adaptively embedded in wavelet coefficients of low-frequency domain. At last, the simulation experimental results show that the algorithm for a variety of conventional image processing has good robustness.

scholarly journals Image Processing Method Based on Chaotic Encryption and Wavelet Transform for Planar Design

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Yiying Liu ◽  
Young Chun Ko
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Chaotic System ◽  
Graphic Design ◽  
Initial Conditions ◽  
Mean Value ◽  
Processing Method ◽  
Chaotic Encryption ◽  
Characteristic Analysis ◽  
The Mean

This paper provides an in-depth study and analysis of image processing for graphic design through chaotic encryption combined with a wavelet transform algorithm. Firstly, the traditional Mallat algorithm is optimized; since the mean value of the transform coefficients generated after the wavelet transform of the image is used as the initial value of the chaotic system to iterate, when the image is modified, then the mean value of the wavelet coefficients will also change, and the final iteration comes out as two different sequences using the property that the chaotic system is extremely sensitive to the initial conditions, so the algorithm has a certain sensitivity to tampering and localization effect. The image of the encrypted graphic design is decrypted by the chaos decryption system, and the final image information of the graphic design is obtained. In terms of the security of the graphic design image itself, the complex dynamical properties of chaos are fully utilized to encrypt it, and the algorithm has a good encryption effect after statistical characteristic analysis, attack complexity, difference analysis, adjacent pixel correlation analysis, and key sensitivity analysis. The plaintext image is decomposed in odd-even sequence using the boosting algorithm to get the sequence with an even index and the sequence with an odd index; then, the diffusion algorithm is applied to the two sequences by the prediction and update algorithm, and this process is repeated many times to get the two ciphertext sequences after scrambling, merging these two sequences, and matrixing them to get the ciphertext image. Finally, the testing of the embedded planar designed image revolves around four aspects, namely, image processing, tamper sensitivity, robustness, and imperceptibility, to examine the designed planar designed image system. In the diffusion manipulation, the key matrix for diffusion is obtained using the threshold processing method of the Local Binary Pattern (LBP) algorithm for the matrices generated by the Logistic Chaos system, which improves the randomness of the algorithm. The experimental results verify the effectiveness and security of the algorithm.

scholarly journals Discrete wavelet transform processing system based on digital watermarking algorithm

2021 ◽  
Vol 2083 (4) ◽  
pp. 042075
Author(s):  
Miao Shi
Keyword(s):  
Image Processing ◽  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Digital Watermarking ◽  
Basic Principle ◽  
Low Frequency ◽  
Processing System ◽  
Discrete Wavelet ◽  
Noise Interference ◽  
Arnold Scrambling

Abstract This paper introduces the concept of multimedia digital watermarking and summarizes the current technology status. This paper summarizes the research status and basic principle of digital watermarking. The advantages of digital watermarking algorithm based on wavelet transform are analyzed. The proposed algorithm combines Arnold scrambling method and DWT transform multi-resolution characteristics, and adopts linear and different embedding strength methods. Effectively improve the security of the watermark. According to the classification results, different intensity watermarking components are embedded into the DCT low frequency coefficients of different image blocks. Experimental results show that this algorithm has strong masking and robustness, and the watermarking realized by using the proposed algorithm has good robustness against common image processing and noise interference.

Automobile Warranty Forecasting Using Wavelet Transform Analysis and Neural Networks

2006 ◽  
Author(s):  
Bharatendra Rai ◽  
Nanua Singh
Keyword(s):  
Neural Networks ◽  
Wavelet Transform ◽  
Low Frequency ◽  
Frequency Resolution ◽  
Frequency Information ◽  
Window Width ◽  
Performance Patterns ◽  
Long Time ◽  
Frequency Components ◽  
Wavelet Transform Analysis

Automobile warranty forecasting is made challenging by ‘maturing data’ (also called warranty growth) phenomena that causes warranty performance at specific months-in-service (MIS) values to change with time. In this paper a wavelet transform based technique is proposed for forecasting the warranty performance in presence of the ‘maturing data’ phenomena. The wavelet transform helps to cut the warranty performance data into different frequency components, and then allow study of each component with a resolution matched to its scale. In other words it allows the use of long time intervals (or longer window widths) for low-frequency information and shorter regions (or shorter window width) for higher-frequency information. The shorter the window width, the better is the resolution. The window widths of the wavelet transform can be adjusted automatically, and provide better time resolution for high frequency components and better frequency resolution for low frequency components of the warranty performance pattern. The proposed approach first decomposes the warranty performance patterns into several scales at different levels of resolution using wavelet transform analysis. The decomposition involves an approximate part from which higher frequency information has been filtered and detail parts from which lower frequency information have been filtered. The chosen approximate and detail parts are extended using neural networks. Subsequently original and the forecasted signals are reconstructed to obtain forecast values for the warranty performance. A real-world application example is used to illustrate the use of the proposed methodology.

Analysis of the 9th November 1990 flare

2000 ◽  
Vol 179 ◽  
pp. 229-232
Author(s):  
Anita Joshi ◽  
Wahab Uddin
Keyword(s):  
Image Processing ◽  
Two Dimensional ◽  
Temporal Behaviour ◽  
Contour Maps ◽  
Dimensional Measurements ◽  
Processing Software ◽  
Image Processing Software

AbstractIn this paper we present complete two-dimensional measurements of the observed brightness of the 9th November 1990Hαflare, using a PDS microdensitometer scanner and image processing software MIDAS. The resulting isophotal contour maps, were used to describe morphological-cum-temporal behaviour of the flare and also the kernels of the flare. Correlation of theHαflare with SXR and MW radiations were also studied.

Specific Labeling of Protein Domains with Antibody Fragments

1981 ◽  
Vol 39 ◽  
pp. 416-417
Author(s):  
U. Aebi ◽  
L.E. Buhle ◽  
W.E. Fowler
Keyword(s):  
Image Processing ◽  
Specific Protein ◽  
Antibody Fragments ◽  
Supramolecular Organization ◽  
Two Dimensional ◽  
Ordered Structures ◽  
Virus Capsids ◽  
Processing Techniques

Many important supramolecular structures such as filaments, microtubules, virus capsids and certain membrane proteins and bacterial cell walls exist as ordered polymers or two-dimensional crystalline arrays in vivo. In several instances it has been possible to induce soluble proteins to form ordered polymers or two-dimensional crystalline arrays in vitro. In both cases a combination of electron microscopy of negatively stained specimens with analog or digital image processing techniques has proven extremely useful for elucidating the molecular and supramolecular organization of the constituent proteins. However from the reconstructed stain exclusion patterns it is often difficult to identify distinct stain excluding regions with specific protein subunits. To this end it has been demonstrated that in some cases this ambiguity can be resolved by a combination of stoichiometric labeling of the ordered structures with subunit-specific antibody fragments (e.g. Fab) and image processing of the electron micrographs recorded from labeled and unlabeled structures.

Shifting perspectives: method, media and the complex image

1998 ◽  
Vol 10 (1-3) ◽  
pp. 100-108 ◽  
Author(s):  
Alicia Colson ◽  
Ross Parry
Keyword(s):  
Image Processing ◽  
Three Dimensional ◽  
Geographical Location ◽  
Spatial Relationship ◽  
Two Dimensional ◽  
Dimensional Approach ◽  
Complex Image ◽  
Cultural Resonance

This article argues that the analysis of a threedimensional image demanded a three-dimensional approach. The authors realise that discussions of images and image processing inveterately conceptualise representation as being flat, static, and finite. The authors recognise the need for a fresh acuteness to three-dimensionality as a meaningful – although problematic – element of visual sources. Two dramatically different examples are used to expose the shortcomings of an ingrained two-dimensional approach and to facilitate a demonstration of how modern (digital) techniques could sanction new historical/anthropological perspectives on subjects that have become all too familiar. Each example could not be more different in their temporal and geographical location, their cultural resonance, and their historiography. However, in both these visual spectacles meaning is polysemic. It is dependent upon the viewer's spatial relationship to the artifice as well as the spirito-intellectual viewer within the community. The authors postulate that the multi- faceted and multi-layered arrangement of meaning in a complex image could be assessed by working beyond the limitations of the two-dimensional methodological paradigm and by using methods and media that accommodated this type of interconnectivity and representation.

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