Relevant bibliographies by topics / Slanlet transform

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Slanlet transform'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "Slanlet transform"

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Hamoud Al-Tamimi, Mohammed Sabbih. "Combining convolutional neural networks and slantlet transform for an effective image retrieval scheme." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 4382. http://dx.doi.org/10.11591/ijece.v9i5.pp4382-4395.

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<p>In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In this
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Mohammed, Sabbih Hamoud Al-Tamimi. "Combining convolutional neural networks and slantlet transform for an effective image retrieval scheme." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 4382–95. https://doi.org/10.11591/ijece.v9i5.pp4382-4395.

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In the latest years there has been a profound evolution in computer science and technology, which incorporated several fields. Under this evolution, Content Base Image Retrieval (CBIR) is among the image processing field. There are several image retrieval methods that can easily extract feature as a result of the image retrieval methods’ progresses. To the researchers, finding resourceful image retrieval devices has therefore become an extensive area of concern. Image retrieval technique refers to a system used to search and retrieve images from digital images’ huge database. In th
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Selesnick, I. W. "The slantlet transform." IEEE Transactions on Signal Processing 47, no. 5 (1999): 1304–13. http://dx.doi.org/10.1109/78.757218.

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Xiang, Xiuqiao, and Baochang Shi. "Evolving generation and fast algorithms of slantlet transform and slantlet-Walsh transform." Applied Mathematics and Computation 269 (October 2015): 731–43. http://dx.doi.org/10.1016/j.amc.2015.07.094.

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Kekre, H. B., Tanuja Sarode, and Shachi Natu. "Performance Comparison of Wavelets Generated from Four Different Orthogonal Transforms for Watermarking With Various Attacks." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 9, no. 3 (2013): 1139–52. http://dx.doi.org/10.24297/ijct.v9i3.3340.

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This paper proposes a watermarking technique using different orthogonal wavelet transforms like Hartley wavelet, Kekrewavelet, Slant wavelet and Real Fourier wavelet transform generated from corresponding orthogonal transform. Theseorthogonal wavelet transforms have been generated using different sizes of component orthogonal transform matrices.For example 256*256 size orthogonal wavelet transform can be generated using 128*128 and 2*2 size componentorthogonal transform. It can also be generated using 64*64 and 4*4, 32*32 and 8*8, 16*16 and 16*16 size componentorthogonal transform matrices. In
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Abbas, Sulaiman M., Mohammed Nadhim Abbas, and Saifuldeen A. Mohammed. "SLANTLET TRANSFORM-BASED OFDM SCHEME." Journal of Engineering 12, no. 03 (2006): 1638–47. http://dx.doi.org/10.31026/j.eng.2006.03.04.

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Wireless digital communication is rapidly expanding resulting in a demand for systems that are reliable and have a high spectral efficiency. To fulfill these demands OFDM technology has drawn a lot of attention. In this paper a new technique is proposed to improve the performance of OFDM. The new technique is use the slantlet transform (SLT) instead Fast Fourier transform (FFT) in order to reduce the level of interference. This also will remove the need for Guard interval (GI) in the case of the FFT-OFDM and therefore improve the bandwidth efficiency of the OFDM. The SLT-OFDM is also better th
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Journal, Baghdad Science. "An Embedded Data Using Slantlet Transform." Baghdad Science Journal 8, no. 3 (2011): 840–48. http://dx.doi.org/10.21123/bsj.8.3.840-848.

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Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and
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Alwan, Iman Mohammed Ga’fer, and Enas Muzaffer Al-Ta’ee. "An Embedded Data Using Slantlet Transform." Baghdad Science Journal 8, no. 3 (2011): 840–48. http://dx.doi.org/10.21123/bsj.2011.8.3.840-848.

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Data hiding is the process of encoding extra information in an image by making small modification to its pixels. To be practical, the hidden data must be perceptually invisible yet robust to common signal processing operations. This paper introduces a scheme for hiding a signature image that could be as much as 25% of the host image data and hence could be used both in digital watermarking as well as image/data hiding. The proposed algorithm uses orthogonal discrete wavelet transforms with two zero moments and with improved time localization called discrete slantlet transform for both host and
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Al-Helali, Adnan Hadi M., Hamza A. Ali, and Buthainah Al-Dulaimi. "Slantlet Transform for Multispectral Image Fusion." Journal of Computer Science 5, no. 4 (2009): 263–69. http://dx.doi.org/10.3844/jcs.2009.263.269.

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Al-Helali. "Slantlet Transform for Multispectral Image Fusion." Journal of Computer Science 5, no. 4 (2009): 263–69. http://dx.doi.org/10.3844/jcssp.2009.263.269.

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Dissertations / Theses on the topic "Slanlet transform"

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Tourshan, Khaled. "Parameterization of slant and slantlet/wavelet transforms with applications /." Thesis, Connect to Dissertations & Theses @ Tufts University, 2003.

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Thesis (Ph.D.)--Tufts University, 2003.<br>Adviser: Joseph P. Noonan. Submitted to the Dept. of Electrical Engineering. Includes bibliographical references (leaves 149-149). Access restricted to members of the Tufts University community. Also available via the World Wide Web;
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Lin, Wen-Zhe, and 林溫哲. "FPGA Realization of Slantlet Transform and Its Applications to Disturbances Detection." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/90837410824585868179.

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碩士<br>國立成功大學<br>電機工程學系碩博士班<br>92<br>In this thesis, the field programmable gate array (FPGA) is employed for the hardware realization of slantlet transform. The realized product is then applied for the disturbance detection. Because the slantlet transform owns a high-performance computation feature that is suitable for the disturbance detection, the thesis is hence motivated to apply such technique for the detection application. In the implementation process, by use of the hardware description language, the slantlet transform algorithm has been embedded into the FPGA chip, which is also furthe
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Li, Ching-Yun, and 李卿雲. "Slant Operational Method for Solving Numerical Inversion of Laplace Transform." Thesis, 2005. http://ndltd.ncl.edu.tw/handle/26041355410496517464.

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碩士<br>真理大學<br>數理科學研究所<br>93<br>The Slant operational matrix of integration is used in this paper to solve the numerical inversion of Laplace transform. First, we derive the Slant operational matrix of integration and set up Slant conversion table, then we could solve the differential equation and the partial differential equation easily. The traditional method is to transfer the differential equation into the algebraic equation via orthogonal function. This paper adopts the advantage of Slant function including: (1) The characteristic that Slant operational matrix of integration changes fa
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Duan, Xiao. "The Fractional Fourier Transform and Its Application to Fault Signal Analysis." Thesis, 2012. http://hdl.handle.net/1969.1/ETD-TAMU-2012-05-11207.

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To a large extent mathematical transforms are applied on a signal to uncover information that is concealed, and the capability of such transforms is valuable for signal processing. One such transforms widely used in this area, is the conventional Fourier Transform (FT), which decomposes a stationary signal into different frequency components. However, a major drawback of the conventional transform is that it does not easily render itself to the analysis of non-stationary signals such as a frequency modulated (FM) or amplitude modulated (AM) signal. The different frequency components of complex
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Books on the topic "Slanlet transform"

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Sabato, Larry J. Feeding frenzy: How attack journalism has transformed American politics. Free Press, 1991.

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Palatnik, Lori. Gossip: Ten Pathways to Eliminate It from Your Life and Transform Your Soul. Health Communications, Incorporated, 2010.

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Feeding frenzy: How attack journalism has transformed American politics. Free Press, 1991.

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Book chapters on the topic "Slanlet transform"

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Rachmawanto, Eko Hari, Lahib Nidhal Dawd, Christy Atika Sari, Rabei Raad Ali, Wisam Subhi Al-Dayyeni, and Mohammed Ahmed Jubair. "Medical Image Watermarking Using Slantlet Transform and Particle Swarm Optimization." In International Conference on Innovative Computing and Communications. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-3010-4_59.

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Barnes, Dustin, Andrew McIntyre, Sui Cheung, John Louie, Emily Hand, and Frederick C. Harris. "Parallelizing the Slant Stack Transform with CUDA." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-70416-2_42.

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Jagtap, Apurwa S., and Revati Shriram. "Performance Parameter Based Comparison of the Slantlet Transform and Discrete Cosine Transform (DCT) for Steganography in Biomedical Signals." In Lecture Notes in Networks and Systems. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8204-7_8.

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Zuo, Jinglong, Delong Cui, Hui Yu, and Qirui Li. "Image Feature Extract and Performance Analysis Based on Slant Transform." In Communications in Computer and Information Science. Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0356-1_52.

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Balaji, V. R., J. Sathiya Priya, J. R. Dinesh Kumar, and S. P. Karthi. "Radial Basis Function Neural Network Based Speech Enhancement System Using SLANTLET Transform Through Hybrid Vector Wiener Filter." In Lecture Notes in Networks and Systems. Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-7345-3_61.

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Nainvarapu, Radha, Ranga Babu Tummala, and Mahesh Kumar Singh. "A Slant Transform and Diagonal Laplacian Based Fusion Algorithm for Visual Sensor Network Applications." In Lecture Notes in Electrical Engineering. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9885-9_15.

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Meenakshi, K., K. Swaraja, Padmavathi Kora, and G. Karuna. "A Robust Watermarking Using RDWT and Slant Transform Using Hybrid Firefly and Differential Evolution Optimization Algorithm." In Lecture Notes in Electrical Engineering. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3690-5_79.

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Kekre, H. B., Sudeep D. Thepade, Arvind Viswanathan, Ashish Varun, Pratik Dhwoj, and Nikhil Kamat. "Palm Print Identification Using Fractional Coefficients of Sine/Walsh/Slant Transformed Palm Print Images." In Communications in Computer and Information Science. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20209-4_30.

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Kekre, H. B., Sudeep D. Thepade, and Ratnesh N. Chaturvedi. "“Color to Gray and Back” Using DST-DCT, Haar-DCT, Walsh-DCT, Hartley-DCT, Slant-DCT, Kekre-DCT Hybrid Wavelet Transforms." In Advances in Intelligent Systems and Computing. Springer India, 2014. http://dx.doi.org/10.1007/978-81-322-1768-8_54.

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Anguh, M. M., and R. R. Martin. "Faster Block Coding of Images using the Truncation Method." In Image Processing: Mathematical Methods and Applications. Oxford University PressOxford, 1997. http://dx.doi.org/10.1093/oso/9780198511977.003.0007.

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Abstract Image compression is widely used in computer graphics; one main method is transform coding of images [l]. For example, the JPEG standard [2] uses Discrete Cosine Transform coding, while the Slant Transform [3] has been used for coding television signals. Other applications have also used Fourier and Walsh Transforms for image compression.
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Conference papers on the topic "Slanlet transform"

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Jasim, Abdulhamed M., Noor Qaqos, Ekenedirichukwu N. Obianom, G. André Ng, and Xin Li. "Effective Hybrid Technique for EcG Signal Denoising Based on Slantlet Transform and Median Filter." In 2024 International Symposium on Electrical, Electronics and Information Engineering (ISEEIE). IEEE, 2024. https://doi.org/10.1109/iseeie62461.2024.00073.

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Mohammed, Rasha Thabit, and Bee Ee Khoo. "Image watermarking using slantlet transform." In 2012 IEEE Symposium on Industrial Electronics and Applications (ISIEA 2012). IEEE, 2012. http://dx.doi.org/10.1109/isiea.2012.6496644.

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Kumar, Sushil, and S. K. Muttoo. "Distortionless Data Hiding Based on Slantlet Transform." In 2009 International Conference on Multimedia Information Networking and Security. IEEE, 2009. http://dx.doi.org/10.1109/mines.2009.263.

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Agaian, Sos S., Khaled Tourshan, and Joseph P. Noonan. "The fast parametric slantlet transform with applications." In Electronic Imaging 2004, edited by Edward R. Dougherty, Jaakko T. Astola, and Karen O. Egiazarian. SPIE, 2004. http://dx.doi.org/10.1117/12.518302.

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Mutt, S. K., and S. Kumar. "Secure image steganography based on Slantlet transform." In 2009 International Conference on Methods and Models in Computer Science (ICM2CS). IEEE, 2009. http://dx.doi.org/10.1109/icm2cs.2009.5397983.

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Ibrahim, Ali K., Hanqi Zhuang, Nurgun Erdol, and Ali Muhmed Ali. "EEG seizure detection by integrating slantlet transform with sparse coding." In 2017 25th European Signal Processing Conference (EUSIPCO). IEEE, 2017. http://dx.doi.org/10.23919/eusipco.2017.8081249.

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Agaian, Sos S., Khaled Tourshan, and Joseph P. Noonan. "Parametric Slant-Hadamard transforms." In Electronic Imaging 2003, edited by Edward R. Dougherty, Jaakko T. Astola, and Karen O. Egiazarian. SPIE, 2003. http://dx.doi.org/10.1117/12.473064.

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Arathi, T., and Latha Prameswaran. "A method for Image representation using Slantlet Transform and Phase Congruency." In the 2014 International Conference. ACM Press, 2014. http://dx.doi.org/10.1145/2660859.2660947.

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Swarnkar, A., Ranjeet Kumar, A. Kumar, and P. Khanna. "Performance of different threshold function for ECG compression using Slantlet transform." In 2017 4th International Conference on Signal Processing and Integrated Networks (SPIN). IEEE, 2017. http://dx.doi.org/10.1109/spin.2017.8049977.

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Ho, Anthony T. S., Xunzhan Zhu, and Jun Shen. "Slant transform watermarking for digital images." In Visual Communications and Image Processing 2003, edited by Touradj Ebrahimi and Thomas Sikora. SPIE, 2003. http://dx.doi.org/10.1117/12.503435.

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