scholarly journals A hybrid pan-sharpening approach using maximum local extrema

2019 ◽  
Vol 9 (1) ◽  
pp. 255
Author(s):  
Prajakta Patil ◽  
C.M. Sheela Rani ◽  
Meenakshi Arya
Keyword(s):  
Real Life ◽  
Quality Measures ◽  
Discrete Wavelet ◽  
Similar Technique ◽  
High Resolution Image ◽  
Digital World ◽  
Inverse Transform ◽  
Local Extrema ◽  
Fused Image ◽  
Fusion Approach

Mixing or combining different elements for getting enhanced version, is practiced across various areas in real life. Pan-sharpening is a similar technique used in the digital world; a process to combine two images into a fused image that comprises more detailed information. Images referred herein are Panchromatic (PAN) and Multispectral (MS) images. This paper presents a pansharpening algorithm which integrates multispectral and panchromatic images to generate an improved multispectral image. This technique merges the Discrete wavelet transform (WT) and Intensity-Hue-Saturation (IHS) through separate fusing criterion for choosing an approximate and detail sub-images. Whereas the maximal local extrema are used for merging detail sub-images and finally merged high-resolution image is reconstructed through inverse transform of wavelet and IHS. The proposed fusion approach enhances the superiority of the resultant fused image is demonstrated by quality measures like CORR, RMSE, PFE, SSIM, SNR and PSNR with the help of satellite Worldview-II images. The proposed algorithm is correlated with the other fusion techniques through empirical outcomes proves the superiority of the final merged image in terms of resolutions than the others.

scholarly journals Multi-focus Image Fusion Using an Effective Discrete Wavelet Transform Based Algorithm

2014 ◽  
Vol 14 (2) ◽  
pp. 102-108 ◽  
Author(s):  
Yong Yang ◽  
Shuying Huang ◽  
Junfeng Gao ◽  
Zhongsheng Qian
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Low Frequency ◽  
Objective Evaluation ◽  
Discrete Wavelet ◽  
Evaluation Indexes ◽  
Fused Image ◽  
Focus Image

Abstract In this paper, by considering the main objective of multi-focus image fusion and the physical meaning of wavelet coefficients, a discrete wavelet transform (DWT) based fusion technique with a novel coefficients selection algorithm is presented. After the source images are decomposed by DWT, two different window-based fusion rules are separately employed to combine the low frequency and high frequency coefficients. In the method, the coefficients in the low frequency domain with maximum sharpness focus measure are selected as coefficients of the fused image, and a maximum neighboring energy based fusion scheme is proposed to select high frequency sub-bands coefficients. In order to guarantee the homogeneity of the resultant fused image, a consistency verification procedure is applied to the combined coefficients. The performance assessment of the proposed method was conducted in both synthetic and real multi-focus images. Experimental results demonstrate that the proposed method can achieve better visual quality and objective evaluation indexes than several existing fusion methods, thus being an effective multi-focus image fusion method.

scholarly journals An innovative image fusion algorithm based on wavelet transform and discrete fast curvelet transform

2011 ◽  
Vol 1 (3) ◽  
Author(s):  
T. Sumathi ◽  
M. Hemalatha
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Curvelet Transform ◽  
Relevant Information ◽  
Good Time ◽  
Discrete Wavelet ◽  
Fusion Algorithm ◽  
Time Frequency ◽  
Fused Image

AbstractImage fusion is the method of combining relevant information from two or more images into a single image resulting in an image that is more informative than the initial inputs. Methods for fusion include discrete wavelet transform, Laplacian pyramid based transform, curvelet based transform etc. These methods demonstrate the best performance in spatial and spectral quality of the fused image compared to other spatial methods of fusion. In particular, wavelet transform has good time-frequency characteristics. However, this characteristic cannot be extended easily to two or more dimensions with separable wavelet experiencing limited directivity when spanning a one-dimensional wavelet. This paper introduces the second generation curvelet transform and uses it to fuse images together. This method is compared against the others previously described to show that useful information can be extracted from source and fused images resulting in the production of fused images which offer clear, detailed information.

FUSION OF SURVEILLANCE IMAGES IN INFRARED AND VISIBLE BAND USING CURVELET, WAVELET AND WAVELET PACKET TRANSFORM

2010 ◽  
Vol 08 (02) ◽  
pp. 271-292 ◽  
Author(s):  
PARUL SHAH ◽  
S. N. MERCHANT ◽  
U. B. DESAI
Keyword(s):  
Wavelet Packet ◽  
Curvelet Transform ◽  
Visual Quality ◽  
Wavelet Packet Transform ◽  
Discrete Wavelet ◽  
Discrete Wavelet Packet Transform ◽  
Fused Image ◽  
Fusion Methods ◽  
Visible Images

This paper presents two methods for fusion of infrared (IR) and visible surveillance images. The first method combines Curvelet Transform (CT) with Discrete Wavelet Transform (DWT). As wavelets do not represent long edges well while curvelets are challenged with small features, our objective is to combine both to achieve better performance. The second approach uses Discrete Wavelet Packet Transform (DWPT), which provides multiresolution in high frequency band as well and hence helps in handling edges better. The performance of the proposed methods have been extensively tested for a number of multimodal surveillance images and compared with various existing transform domain fusion methods. Experimental results show that evaluation based on entropy, gradient, contrast etc., the criteria normally used, are not enough, as in some cases, these criteria are not consistent with the visual quality. It also demonstrates that the Petrovic and Xydeas image fusion metric is a more appropriate criterion for fusion of IR and visible images, as in all the tested fused images, visual quality agrees with the Petrovic and Xydeas metric evaluation. The analysis shows that there is significant increase in the quality of fused image, both visually and quantitatively. The major achievement of the proposed fusion methods is its reduced artifacts, one of the most desired feature for fusion used in surveillance applications.

scholarly journals MENELISIK SIASAT CERITA DIGITAL REALITY PADA FILM READY PLAYER ONE?

2019 ◽  
Vol 5 (02) ◽  
pp. 159
Author(s):  
Jokhanan Kristiyono ◽  
Hernani Sirikit
Keyword(s):  
New Media ◽  
Communication Technology ◽  
Narrative Analysis ◽  
Real Life ◽  
Research Problem ◽  
Human Beings ◽  
Steven Spielberg ◽  
Digital World ◽  
History Of ◽  
Digital Film

<p>ABSTRACT</p><p>This study aims to find out how factual and digital reality are depicted in film.Castells’ theory on new media is taken for the base theory, subjectivity-identity and power and knowledge by Foucault. Narrative analysis by Lacey is applied to seek answer for the research problem. The advancement of Communication Technology has enabled human beings to have freedom in imagination and make it real. Digital technology and virtual realm are enriched with emerging faked realities and identities. Film, becomes a platform for practising this kind of freedom, making fantasy feels like reality. Film Ready Player One? directed by Steven Spielberg depicts real and virtual world. This study aims to elaborate how real life and digital life are narrated and described in this film. A new identity created in The OASIS,the digital world that a place where mankind escape from reality. Units to be analysed in eight structures of analysis are story, plot, and character. Concludesis factual reality and digital reality are described well in this film, it even tends to hyper-reality. Moreover, conflict in digital world and in the future (2045) are still the same with problems in the history of mankind.</p><p>Keywords; Film; Digital reality; Identities; Narrative.</p><p>ABSTRAK</p><p>Penelitian ini bertujuan mengetahui bagaimana realitas faktual dan realitas digital digambarkan dalam film. Menggunakan teori new media Castells, subjektivitas dan identitas serta power dan knowledge Foucault. Penelitian film ini menggunakan pendekatan deskriptif kualitatif, dengan metode Analisa Naratif Film (Lacey, 2017). Kemajuan teknologi informasi dan komunikasi membuat manusia memiliki keleluasaan dalam berimajinasi dan merealisasikannya. Teknologi digital dan alam virtual semakin diperkaya dengan munculnya realitas dan identitas semu. Film, sebagai salah satu medium komunikasi massa, merupakan wadah kebebasan berimajinasi. Film Ready Player One?.Film besutan sutradara Steven Spielberg menggambarkan pergesekan antara dunia nyata dan dunia digital. Film ini menunjukkan kehidupan masyarakat moderen pada tahun 2045, dengan adanya perkembangan teknologi yang luar biasa. Suatu piranti yang mengubah manusia menjadi sangat tergantung dengan teknologi. Teknologi informasi dan komunikasi yang menciptakan dunia baru yaitu dunia digital. OASIS, dunia tempat pelarian manusia modern dan menciptakan identitas baru yaitu identitas virtual. Masyarakat informasi yang menciptakan realitas digital. Unit analisis story, plot, dan karakter dianalisis secara naratif dengan delapan struktur. Hasil analisis memberikan jawaban bahwa realitas nyata dan realitas digital digambarkan secara baik dalam film ini, bahkan cenderung berlebihan (hyper-reality). Selain itu, konflik di dunia digital di tahun 2045 tetap sama dengan konflik dalam sejarah manusia.</p><p>Kata Kunci; Film; Digital Reality; Identitas; Naratif.</p>

Data Clustering Using Sine Cosine Algorithm

2017 ◽  
pp. 715-726 ◽  
Author(s):  
Vijay Kumar ◽  
Dinesh Kumar
Keyword(s):  
Real Life ◽  
Quality Measures ◽  
Search Space ◽  
Search Method ◽  
Local Optima ◽  
Encoding Scheme ◽  
Clustering Techniques ◽  
Sine Cosine Algorithm ◽  
Cluster Quality ◽  
Optimal Cluster

The clustering techniques suffer from cluster centers initialization and local optima problems. In this chapter, the new metaheuristic algorithm, Sine Cosine Algorithm (SCA), is used as a search method to solve these problems. The SCA explores the search space of given dataset to find out the near-optimal cluster centers. The center based encoding scheme is used to evolve the cluster centers. The proposed SCA-based clustering technique is evaluated on four real-life datasets. The performance of SCA-based clustering is compared with recently developed clustering techniques. The experimental results reveal that SCA-based clustering gives better values in terms of cluster quality measures.

The Second Life of Judaism: A History of Religious Community and Practice in Virtual Spaces

2019 ◽  
pp. 235-260
Author(s):  
Julian Voloj ◽  
Anthony Bak Buccitelli
Keyword(s):  
San Francisco ◽  
Second Life ◽  
Cultural Practices ◽  
Real Life ◽  
Virtual Space ◽  
Religious Community ◽  
Digital World ◽  
The People ◽  
History Of ◽  
Religious Cultures

This chapter talks about San Francisco-based company Linden Lab who launched Second Life (SL), which is described as an online digital world that is built, shaped, and owned by its participants. It discloses how SL was seen as the next big internet phenomenon and was the focus of attention by investors and media alike for a short period of time. It also explains SL's complex relationship with 'real life', which is defined both by the encoded parameters of the virtual space and by the social and cultural practices of the people who use the platform. The chapter discusses SL as a broad platform that encompassed many cultural constructions and developed a rich and diverse set of religious cultures. It recounts how dozens of Jewish sites across the grid emerged and were created both by individual users and by offline institutions that established SL presences.

scholarly journals A Multi-Valued Diagnostic Model Synthesis Based on Descrete Wavelet Transform

2015 ◽  
Vol 27 (1) ◽  
pp. 43-52 ◽  
Author(s):  
Henryk Borowczyk
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
High Frequency ◽  
Real Life ◽  
Signal Decomposition ◽  
Diagnostic Model ◽  
Discrete Wavelet ◽  
Model Synthesis ◽  
Vibroacoustic Signal ◽  
Three Stages

Abstract The method of a multi-valued diagnostic model synthesis using discrete wavelet transform is presented. The method's algorithm consists of three stages: (1) - signal decomposition into low- and high frequency parts - approximations and details, (2) - approximations and details parameterization, (3) - multi-valued encoding parameters obtained in stage 2. The method is illustrated with vibroacoustic signal in real life experiment. The multi-valued diagnostic model is the final result.

scholarly journals Airborne Infrared and Visible Image Fusion for Target Perception Based on Target Region Segmentation and Discrete Wavelet Transform

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Yifeng Niu ◽  
Shengtao Xu ◽  
Lizhen Wu ◽  
Weidong Hu
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Discrete Wavelet Transform ◽  
Discrete Wavelet ◽  
Infrared Images ◽  
Target Information ◽  
Visible Image ◽  
Region Segmentation ◽  
Target Region ◽  
Fused Image

Infrared and visible image fusion is an important precondition of realizing target perception for unmanned aerial vehicles (UAVs), then UAV can perform various given missions. Information of texture and color in visible images are abundant, while target information in infrared images is more outstanding. The conventional fusion methods are mostly based on region segmentation; as a result, the fused image for target recognition could not be actually acquired. In this paper, a novel fusion method of airborne infrared and visible image based on target region segmentation and discrete wavelet transform (DWT) is proposed, which can gain more target information and preserve more background information. The fusion experiments are done on condition that the target is unmoving and observable both in visible and infrared images, targets are moving and observable both in visible and infrared images, and the target is observable only in an infrared image. Experimental results show that the proposed method can generate better fused image for airborne target perception.

EEG Signals Classification Using Support Vector Machine

2020 ◽  
Vol 12 (2) ◽  
pp. 215-224
Author(s):  
Abdelhakim Ridouh ◽  
Daoud Boutana ◽  
Salah Bourennane
Keyword(s):  
Support Vector Machine ◽  
Wavelet Decomposition ◽  
Moving Average ◽  
Real Life ◽  
Support Vector ◽  
Discrete Wavelet ◽  
Eeg Signal ◽  
Eeg Signals ◽  
Decomposition Level ◽  
Sensitivity Specificity

We address with this paper some real-life healthy and epileptic EEG signals classification. Our proposed method is based on the use of the discrete wavelet transform (DWT) and Support Vector Machine (SVM). For each EEG signal, five wavelet decomposition level is applied which allow obtaining five spectral sub-bands correspond to five rhythms (Delta, Theta, Alpha, Beta and gamma). After the extraction of some features on each sub-band (energy, standard deviation, and entropy) a moving average (MA) is applied to the resulting features vectors and then used as inputs to SVM to train and test. We test the method on EEG signals during two datasets: normal and epileptics, without and with using MA to compare results. Three parameters are evaluated such as sensitivity, specificity, and accuracy to test the performances of the used methods.

A Novel Image Fusion Approach Based on Rough Set and Wavelet Analysis

2010 ◽  
Vol 439-440 ◽  
pp. 1069-1074 ◽  
Author(s):  
Zhi Yong Zhu
Keyword(s):  
Wavelet Transform ◽  
Image Fusion ◽  
Rough Set ◽  
Wavelet Coefficients ◽  
Absolute Value ◽  
High Quality Image ◽  
Quality Image ◽  
Fused Image ◽  
Fusion Scheme ◽  
Fusion Approach

The goal of image fusion is to combine a high-quality image from multi-image about the same object. The paper presents an image fusion scheme based on wavelet transform and rough set. Firstly, the two images are decomposed by orthogonal wavelet; the image’s wavelet coefficients are got. Comparing with the two image’s wavelet coefficients, wavelet coefficients’ matrix is composed of maximum absolute value, the fused image is obtained by the inverse wavelet transform. The last section of the paper verifies the method by experiment and gets the good experimental results.

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