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Journal articles on the topic 'Integer Wavelet Transform'

Author: Grafiati

Published: 4 June 2021

Last updated: 25 July 2025

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1

Dewitte, S., and J. Cornelis. "Lossless integer wavelet transform." IEEE Signal Processing Letters 4, no. 6 (1997): 158–60. http://dx.doi.org/10.1109/97.586035.

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2

NAVARRO, JAIME, and OSCAR HERRERA. "CONVERGENCE OF THE DISCRETE WAVELET TRANSFORM." International Journal of Wavelets, Multiresolution and Information Processing 10, no. 06 (2012): 1250060. http://dx.doi.org/10.1142/s0219691312500609.

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The discrete wavelet transform; depending of the pair of integers (m, n), applied to functions f in L2(R) with respect to an admissible function h in L2(R) of class C∞ with compact support, is used to prove that f is continuous at x = 0, and furthermore at any x = b in R if and only if there exists the convergence of the discrete wavelet transform, as (m, n) → (-∞, n1) for any integer n1.

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3

Zhang, Ding Hui, Yu Ping Wang, Jian Wei Zhang, Sai Sai Xu, and You Li. "Blind Digital Watermarking of Integer Wavelet Transform." Advanced Materials Research 433-440 (January 2012): 5962–66. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.5962.

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In the light of JPEG compression attack, a blind digital watermarking algorithm of integer wavelet transform is proposed in this paper. Before the watermarking image is embedded, the cover image is decomposed by integer wavelet transform, and the binary watermarking image is scrambled to enhance its security. The scrambled digital watermarking is embedded into the cover image by means of modulo operation and modification of the integer wavelet transform coefficients of the cover image. The digital watermarking is extracted only by means of the modulo operation of the integer wavelet transform

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4

Wang, Bin. "Reversible Integer Wavelet Transform for the Joint of Image Encryption and Watermarking." Mathematical Problems in Engineering 2015 (2015): 1–11. http://dx.doi.org/10.1155/2015/935741.

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In recent years, signal processing in the encrypted domain has attracted considerable research interest, especially embedding watermarking in encrypted image. In this work, a novel joint of image encryption and watermarking based on reversible integer wavelet transform is proposed. Firstly, the plain-image is encrypted by chaotic maps and reversible integer wavelet transform. Then the lossless watermarking is embedded in the encrypted image by reversible integer wavelet transform and histogram modification. Finally an encrypted image containing watermarking is obtained by the inverse integer w

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5

Wei, Xiaopeng, Bin Wang, Qiang Zhang, and Chao Che. "Image Encryption based on Chaotic Map and Reversible Integer Wavelet Transform." Journal of Electrical Engineering 65, no. 2 (2014): 90–96. http://dx.doi.org/10.2478/jee-2014-0013.

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Abstract In recent years, there has been growing interesting in image encryption based on chaotic maps and wavelet transform. In this paper, a novel scheme for image encryption based on chaotic maps and reversible integer wavelet transform is proposed. Firstly, the cipher key which is related to plain-image is used to generate different parameters and initial values of chaotic maps. Then the plain-image is permuted by the order from chaotic maps, and processed by integer wavelet transform. A part of transform coefficient is diffused by the orbits of chaotic maps. Finally, the cipher image is o

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6

Bhat, Younus. "Generalized inequalities for nonuniform wavelet frames in linear canonical transform domain." Filomat 37, no. 12 (2023): 3725–35. http://dx.doi.org/10.2298/fil2312725b.

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A constructive algorithm based on the theory of spectral pairs for constructing nonuniform wavelet basis in L2(R) was considered by Gabardo and Nashed. In this setting, the associated translation set is a spectrum ? which is not necessarily a group nor a uniform discrete set, given ? = {0, r/N} + 2Z, where N ? 1 (an integer) and r is an odd integer with 1 ? r ? 2N?1 such that r and N are relatively prime and Z is the set of all integers. In this article, we continue this study based on non-standard setting and obtain some inequalities for the nonuniform wavelet system {f?j,?(x) = (2N)j/2f((2N)

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Toda, Hiroshi, Zhong Zhang, and Takashi Imamura. "Perfect-translation-invariant variable-density complex discrete wavelet transform." International Journal of Wavelets, Multiresolution and Information Processing 12, no. 04 (2014): 1460001. http://dx.doi.org/10.1142/s0219691314600017.

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The theorems giving the conditions for discrete wavelet transforms (DWTs) to achieve perfect translation invariance (PTI) have already been proven, and based on these theorems, the dual-tree complex DWT and the complex wavelet packet transform, achieving PTI, have already been proposed. However, there is not so much flexibility in their wavelet density. In the frequency domain, the wavelet density is fixed by octave filter banks, and in the time domain, each wavelet is arrayed on a fixed coordinate, and the wavelet packet density in the frequency domain can be only designed by dividing an octa

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8

Nagendran, R., and A. Vasuki. "Hyperspectral image compression using hybrid transform with different wavelet-based transform coding." International Journal of Wavelets, Multiresolution and Information Processing 18, no. 01 (2019): 1941008. http://dx.doi.org/10.1142/s021969131941008x.

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Hyperspectral image resolution offers limited spectral bands within a continual spectral spectrum, creating one of the spectra of most pixels inside the sequence which contains huge volume of data. Data transmission and storage is a challenging task. Compression of hyperspectral images are inevitable. This work proposes a Hyperspectral Image (HSI) compression using Hybrid Transform. First the HSI is decomposed into 1D and it is clustered and tiled. Each cluster is applied with Integer Karhunen–Loeve Transform (IKLT) and as such it is applied for whole image to get IKLT bands in spectral dimens

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9

Lee, Sunil, Chang D. Yoo, and Ton Kalker. "Reversible Image Watermarking Based on Integer-to-Integer Wavelet Transform." IEEE Transactions on Information Forensics and Security 2, no. 3 (2007): 321–30. http://dx.doi.org/10.1109/tifs.2007.905146.

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10

Chen, Renxi, and Xinhui Li. "DEM compression based on integer wavelet transform." Geo-spatial Information Science 10, no. 2 (2007): 133–36. http://dx.doi.org/10.1007/s11806-007-0038-8.

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11

P. N. Kota, P. B. Chopade,. "IMAGE RESOLUTION ENHANCEMENT OF SATELLITE IMAGES USING DYADIC INTEGER COEFFICIENT WAVELET FILTER FOR WAVELET TRANSFORM." INFORMATION TECHNOLOGY IN INDUSTRY 9, no. 1 (2021): 971–75. http://dx.doi.org/10.17762/itii.v9i1.225.

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In this paper, image resolution enhancements for satellite images are proposed using dyadic integer coefficients based wavelet filter (DICWF). We proposes a technique in which discrete wavelet transform and stationary wavelet transform using DICWF which is used to obtain a high resolution image and this image is derived from frequency subbands. The satellite images play a very vital role now days in the development of technical aspects which needs to be enhanced. These satellite images are superresolved with the help of dyadic integer coefficient-based wavelet filters, which reduces the hardwa

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12

Ravi, Ranjan, Thirani Subham, Pemeena Priyadarsini M.Jasmine, G.K.Rajini, and A.Jabeena. "A Juxtaposition Between Integer Wavelet Transform and Discrete Wavelet Transform for Secure Image Steganography." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 5 (2020): 1019–23. https://doi.org/10.35940/ijeat.E9639.069520.

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Image steganography is a technique that is used to hide information. The information can be of various types like image, video, or audio. Steganography is done so that no one apart from the correct receiver can retrieve the information. This paper consists of all advantages and highlights of the wavelet transform but with the additional features like randomness and some default values that are already built-in it. Various algorithms can be used in steganography and they provide good hiding capacity and low detectability. Here we have hidden the image into the cover image using Integer Wavelet

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13

K.A, Neena, Aiswriya Raj, and Rajesh Cherian Roy. "Image Enhancement based on Stationary Wavelet Transform, Integer Wavelet Transform and Singular Value Decomposition." International Journal of Computer Applications 58, no. 11 (2012): 30–35. http://dx.doi.org/10.5120/9327-3632.

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14

Guo, Rui, Yu Feng Li, and Fei Liu. "Image Compression Technology Reseach Based on Lifting Wavelet Transform." Advanced Materials Research 989-994 (July 2014): 3910–14. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.3910.

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Because the operational speed of the traditional image compression based on Mallat algorithm is slow, and auxiliary Storage space is occupied, image compressed method based on lifting wavelet transform is proposed, in order to realize its versatility, flexibility and high efficient. Experiments show that the lifting wavelet transform, is easy to realize integer wavelet transform can be used for lossless compression, and has higher compression ratio.

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15

Fahad, Layth Malallah, Ali Jafaar Awatif, Hasan Abbas Nidaa, and Ghanem Saeed Mustafa. "Reversible color video watermarking scheme based on hybrid of integer-to-integer wavelet transform and Arnold transform." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (2020): 3519–27. https://doi.org/10.11591/ijece.v10i4.pp3519-3527.

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Unauthorised redistribution and illegal copying of digital contents are serious issues which have affected numerous types of digital contents such as digital video. One of the methods which have been suggested to support copyright protectionis to hide digital watermark within the digital video. This paper introduces a new video watermarking system which based on a combination of Arnold transform and integer wavelet transforms (IWT). IWT is employed to decompose the cover video frames whereby Arnold transform is used to scramble the watermark which is a grey scale image. Scrambling the watermar

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16

AVINASHIAPPAN, AMSAVENI, BHARATHI MAYILSAMY, and JUDE HEMANTH DURAISAMY. "SECURITY ENHANCED ROI BASED REVERSIBLE WATERMARKING FOR MEDICAL IMAGES." DYNA 97, no. 2 (2022): 210–16. http://dx.doi.org/10.6036/10148.

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The ever-increasing number of digital medical images and the need to exchange them between medical experts and hospitals for a better and more precise diagnosis demand that the privacy of patients be protected. As a result, medical images sent over the internet must be watermarked with the patient's information so that doctors can validate the medical image. In this research article, a novel watermarking scheme combining two techniques, Difference Expansion and Integer-to-Integer wavelet transformation is proposed. The patient data is inserted into ROI1 using difference expansion and the ROI1

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17

Xuan, Guorong, Jiang Zhu, Jidong Chen, Yun Q. Shi, Zhicheng Ni, and Wei Su. "Distortionless data hiding based on integer wavelet transform." Electronics Letters 38, no. 25 (2002): 1646. http://dx.doi.org/10.1049/el:20021131.

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18

Hemalatha, S., U. Dinesh Acharya, and A. Renuka. "Audio data hiding technique using integer wavelet transform." International Journal of Electronic Security and Digital Forensics 8, no. 2 (2016): 131. http://dx.doi.org/10.1504/ijesdf.2016.075586.

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19

Kapadia, Amishi Mahesh, and Nithyanandam Pandian. "Reversible data hiding methods in integer wavelet transform." International Journal of Information and Computer Security 12, no. 1 (2020): 70. http://dx.doi.org/10.1504/ijics.2020.104001.

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20

Kapadia, Amishi Mahesh, and Nithyanandam Pandian. "Reversible data hiding methods in Integer Wavelet Transform." International Journal of Information and Computer Security 11, no. 1 (2019): 1. http://dx.doi.org/10.1504/ijics.2019.10014436.

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21

Chengjiang Lin, Bo Zhang, and Y. F. Zheng. "Packed integer wavelet transform constructed by lifting scheme." IEEE Transactions on Circuits and Systems for Video Technology 10, no. 8 (2000): 1496–501. http://dx.doi.org/10.1109/76.889059.

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22

Wang, Xi-zhen, Yun-tian Teng, Meng-tan Gao, and Hui Jiang. "Seismic data compression based on integer wavelet transform." Acta Seismologica Sinica 17, S1 (2004): 123–28. http://dx.doi.org/10.1007/s11589-004-0075-4.

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23

Cai, Ming, Wenxiao Qiao, Xiaodong Ju, Xiaohua Che, and Yuhong Zhao. "Lossless compression method for acoustic waveform data based on wavelet transform and bit-recombination mark coding." GEOPHYSICS 78, no. 5 (2013): V219—V228. http://dx.doi.org/10.1190/geo2012-0290.1.

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In well logging, large amounts of data need to be sent from downhole to the surface by means of a very band-limited telemetry system. The limited bandwidth usually results in prolonging of expensive rig time and/or the sacrifice of borehole information. Data compression techniques, to some extent, may relieve this problem. We deduced the adaptive (4, 4) lifting integer-to-integer wavelet transform formula and its inverse transform formula based on the basic principle of wavelet transform, and we explored an appropriate bit-recombination mark coding approach according to the characteristics of

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24

Malallah, Fahad Layth, Awatif Ali Jafaar, Nidaa Hasan Abbas, and Mustafa Ghanem Saeed. "Reversible color video watermarking scheme based on hybrid of integer-to-integer wavelet transform and Arnold transform." International Journal of Electrical and Computer Engineering (IJECE) 10, no. 4 (2020): 3519. http://dx.doi.org/10.11591/ijece.v10i4.pp3519-3527.

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<p>Unauthorized redistribution and illegal copying of digital contents are serious issues which have affected numerous types of digital contents such as digital video. One of the methods, which have been suggested to support copyright protection, is to hide digital watermark within the digital video. This paper introduces a new video watermarking system which based on a combination of Arnold transform and integer wavelet transforms (IWT). IWT is employed to decompose the cover video frames whereby Arnold transform is used to scramble the watermark which is a grey scale image. Scrambling

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25

Li, Yuan-Min, Yang Deng, Mingjie Jiang, and Deyun Wei. "Fast Encryption Algorithm Based on Chaotic System and Cyclic Shift in Integer Wavelet Domain." Fractal and Fractional 8, no. 2 (2024): 75. http://dx.doi.org/10.3390/fractalfract8020075.

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This paper introduces a new fast image encryption scheme based on a chaotic system and cyclic shift in the integer wavelet domain. In order to increase the effectiveness and security of encryption, we propose a new diffusion scheme by using bidirectional diffusion and cyclic shift and apply it to our encryption scheme. First, a two-level integer wavelet transform is used to split the plaintext picture into four low-frequency components. Second, we use random sequences generated by Chen’s hyper-chaotic system to scramble four low-frequency components. The initial value is determined by Secure H

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26

Taheri, Ayoub. "Hybrid and Invisible Digital Image Watermarking Technique Using IWT-DCT and Hopfield Neural Network." Iraqi Journal for Electrical and Electronic Engineering 19, no. 2 (2023): 18–24. http://dx.doi.org/10.37917/ijeee.19.2.3.

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According to the characteristic of HVS (Human Visual System) and the association memory ability of the neural network, an adaptive image watermarking algorithm based on a neural network is proposed invisible image watermarking is a secret embedding scheme for hiding secret images into a cover image file and the purpose of invisible watermarking is copyrights protection. Wavelet transformation-based image watermarking techniques provide better robustness for statistical attacks in comparison to Discrete Cosine Transform domain-based image watermarking. The joined method of IWT (Integer Wavelet

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27

Qiang, Zheng Jie, and He Xin Zhang. "Laser Active Image De-Noising Algorithm Based on Lifting-Wavelet." Advanced Materials Research 1044-1045 (October 2014): 1194–200. http://dx.doi.org/10.4028/www.scientific.net/amr.1044-1045.1194.

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According to the characteristics of laser active imaging and the real-time image features needed, a new image de-noising algorithm based on the voting median filter and integer lifting-wavelet transform was proposed. Firstly, the noise image was dealt with voting median filter to eliminate the interference of impulse noise. Secondly, the noise image was decomposed with lifting-wavelet, wavelet coefficients was processed with Bayes adaptive threshold method. Finally got de-noised image by inverse transform. Through compared with the standard median filter, lifting-wavelet transform, the ordinar

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28

Tan, Huisheng. "FPGA implementation of multilevel two-dimension integer wavelet transform." JOURNAL OF ELECTRONIC MEASUREMENT AND INSTRUMENT 2009, no. 7 (2009): 29–34. http://dx.doi.org/10.3724/sp.j.1187.2009.07029.

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29

Muhammad, Nazeer, Nargis Bibi, Zahid Mahmood, Tallha Akram, and Syed Rameez Naqvi. "Reversible integer wavelet transform for blind image hiding method." PLOS ONE 12, no. 5 (2017): e0176979. http://dx.doi.org/10.1371/journal.pone.0176979.

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30

Ajeeshvali, N., and B. Rajasekhar. "Steganography Based on Integer Wavelet Transform and Bicubic Interpolation." International Journal of Image, Graphics and Signal Processing 4, no. 12 (2012): 26–33. http://dx.doi.org/10.5815/ijigsp.2012.12.04.

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31

Nizampatnam, Prasad, and Kishore Kumar Tappeta. "Bandwidth extension of narrowband speech using integer wavelet transform." IET Signal Processing 11, no. 4 (2017): 437–45. http://dx.doi.org/10.1049/iet-spr.2016.0453.

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32

Delforouzi, Ahmad, and Mohammad Pooyan. "Adaptive Digital Audio Steganography Based on Integer Wavelet Transform." Circuits, Systems & Signal Processing 27, no. 2 (2008): 247–59. http://dx.doi.org/10.1007/s00034-008-9019-x.

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33

Al-Sulaifanie, A. K., A. Ahmadi, and M. Zwolinski. "Very large scale integration architecture for integer wavelet transform." IET Computers & Digital Techniques 4, no. 6 (2010): 471–83. http://dx.doi.org/10.1049/iet-cdt.2009.0021.

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34

Miri, Aref, and Karim Faez. "An image steganography method based on integer wavelet transform." Multimedia Tools and Applications 77, no. 11 (2017): 13133–44. http://dx.doi.org/10.1007/s11042-017-4935-z.

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35

Liji, C. A., K. P. Indiradevi, and K. K. Anish Babu. "Integer-to-Integer Wavelet Transform Based ECG Steganography for Securing Patient Confidential Information." Procedia Technology 24 (2016): 1039–47. http://dx.doi.org/10.1016/j.protcy.2016.05.230.

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36

ASHINO, RYUICHI, TAKESHI MANDAI, and AKIRA MORIMOTO. "BLIND SOURCE SEPARATION OF SPATIO-TEMPORAL MIXED SIGNALS USING PHASE INFORMATION OF ANALYTIC WAVELET TRANSFORM." International Journal of Wavelets, Multiresolution and Information Processing 08, no. 04 (2010): 575–94. http://dx.doi.org/10.1142/s0219691310003651.

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The cocktail party problem deals with the specialized human listening ability to focus one's listening attention on a single talker among a cacophony of conversations and background noises. The blind source separation problem is how to enable computers to solve the cocktail party problem in a satisfactory manner. The simplest version of spatio-temporal mixture problem, which is a type of blind source separation problem, has been solved by a generalized version of the quotient signal estimation method based on the analytic wavelet transform, under the assumption that the time delays are integer

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37

Liu, Hanlin, Jingju Liu, Xuehu Yan, Pengfei Xue, and Dingwei Tan. "An Audio Steganography Based on Run Length Encoding and Integer Wavelet Transform." International Journal of Digital Crime and Forensics 13, no. 2 (2021): 16–34. http://dx.doi.org/10.4018/ijdcf.2021030102.

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This paper proposes an audio steganography method based on run length encoding and integer wavelet transform which can be used to hide secret message in digital audio. The major contribution of the proposed scheme is to propose an audio steganography with high capacity, where the secret information is compressed by run length encoding. In the applicable scenario, the main purpose is to hide as more information as possible in the cover audio files. First, the secret information is chaotic scrambling, then the result of scrambling is run length encoded, and finally, the secret information is emb

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38

Shabina, Shaik, Ravipati Iswarya Lakshmi, Shaik Arshia, Vemuri Harshitha, and Rayachoti Eswariah. "Image Steganography Using Integer Wavelet Transform and Singular Value Decomposition." International Journal of Computer Sciences and Engineering 7, no. 3 (2019): 967–71. http://dx.doi.org/10.26438/ijcse/v7i3.967971.

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39

Orachon, Teerapong. "Non-Separable 3D Integer Wavelet Transform for Lossless Data Compression." Science Journal of Circuits, Systems and Signal Processing 3, no. 6 (2014): 35. http://dx.doi.org/10.11648/j.cssp.20140306.11.

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40

Unser, M., A. Aldroubi, and S. J. Schiff. "Fast implementation of the continuous wavelet transform with integer scales." IEEE Transactions on Signal Processing 42, no. 12 (1994): 3519–23. http://dx.doi.org/10.1109/78.340787.

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41

Mukherjee, Tilak, B. Y. V. N. R. Swamy, and M. V. L. Bhavani. "Robust Image Compression using Integer Wavelet Transform Exploiting Lifting Scheme." International Journal of Engineering Trends and Technology 7, no. 5 (2014): 217–20. http://dx.doi.org/10.14445/22315381/ijett-v7p256.

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42

Kadhim, Mohammed Ayad, and Majid Jabbar Jawad. "A Coverless Video Steganography Technique Based on Integer Wavelet Transform." Ingénierie des systèmes d information 29, no. 5 (2024): 1991–97. http://dx.doi.org/10.18280/isi.290530.

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43

Huang, Chin-Pan. "Sharing secret images using integer single or multiple wavelet transform." Journal of Communications Technology and Electronics 56, no. 1 (2011): 43–51. http://dx.doi.org/10.1134/s1064226910121046.

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44

Reichel, J., G. Menegaz, M. J. Nadenau, and M. Kunt. "Integer wavelet transform for embedded lossy to lossless image compression." IEEE Transactions on Image Processing 10, no. 3 (2001): 383–92. http://dx.doi.org/10.1109/83.908504.

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45

Wang, Xiang Shi. "Research on the Algorithm for Parallel Computing Based on Lifting Wavelet Transform." Advanced Materials Research 912-914 (April 2014): 1365–68. http://dx.doi.org/10.4028/www.scientific.net/amr.912-914.1365.

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In this paper we proposed the new method of a lifting wavelet transform accoding to the characteristics of the parallel computing hardware units in practial application. We improved the mode of integer to construct a new 5/3 wavelet transform scheme .In order to validate the effectiveness of the proposed method applying the new method to the image and compare the result obtained using the traditional transform by the MSE evaluation. Experimental results show that the proposed method is superior and reducing the number of computations and the large capacity storage that restrict the implementat

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46

Shyamala, N., and Dr S. Geetha. "Compression of Medical Images Using Wavelet Transform and Metaheuristic Algorithm for Telemedicine Applications." International Journal of Electrical and Electronics Research 10, no. 2 (2022): 161–66. http://dx.doi.org/10.37391/ijeer.100219.

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Medical image compression becomes necessary to efficiently handle huge number of medical images for storage and transmission purposes. Wavelet transform is one of the popular techniques widely used for medical image compression. However, these methods have some limitations like discontinuity which occurs when reducing image size employing thresholding method. To overcome this, optimization method is considered with the available compression methods. In this paper, a method is proposed for efficient compression of medical images based on integer wavelet transform and modified grasshopper optimi

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47

Suryadi, Suryadi Suryadi. "PENGAMANAN DATA DIGITAL MENGGUNAKAN TEKNIK INTEGER WAVELET TRANSFORM DAN LEAST SIGNIFICANT BIT." Jurnal Ilmu Kepolisian 17, no. 1 (2023): 19. http://dx.doi.org/10.35879/jik.v17i1.375.

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AbstractData is an asset for all parties. So that it must always be guarded or secured so that it is not misused by irresponsible parties. One of the methods used for data security is steganography. In this paper, efforts to secure data are discussed through the development of steganographic algorithms using the Haar integer wavelet transform (IWT-Haar) and least significant bit (LSB) techniques to hide secret messages in the form of digital text into digital images (cover images) to produce stego images. The results show that the extracting process is much faster than the embedding process. T

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48

Anushree, Srivastava* Narendra Kumar Chaurasia. "COMPRESSING BIOMEDICAL IMAGE BY USING INTEGER WAVELET TRANSFORM AND PREDICTIVE ENCODER." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 5, no. 8 (2016): 517–23. https://doi.org/10.5281/zenodo.60094.

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Image compression has become an important process in today’s world of information exchange. It helps in effective utilization of high speed network resources. Medical image compression has an important role in medical field because they are used for future reference of patients. Medical data is compressed in such a way so that the diagnostics capabilities are not compromised or no medical information is lost. Medical imaging poses the great challenge of having compression algorithms that reduce the loss of fidelity as much as possible so as not to contribute to diagnostic errors and yet

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49

Bennilo Fernandes, J., N. Prabakaran, G. Thirugnanam, and Sivakannan Subramani. "Robust medical image watermarking technique using integer wavelet transform and shearlet transform with BSVD." International Journal of Advanced Intelligence Paradigms 19, no. 1/2 (2021): 1. http://dx.doi.org/10.1504/ijaip.2021.10024078.

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50

Alotaibi, Reem A., and Lamiaa A. Elrefaei. "Text-image watermarking based on integer wavelet transform (IWT) and discrete cosine transform (DCT)." Applied Computing and Informatics 15, no. 2 (2019): 191–202. http://dx.doi.org/10.1016/j.aci.2018.06.003.

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