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Статті в журналах з теми "Bit plane"

Автор: Grafiati

Опубліковано: 30 травня 2022

Оновлено: 31 липня 2025

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1

Kim, Jungrae, Michael Sullivan, Esha Choukse, and Mattan Erez. "Bit-plane compression." ACM SIGARCH Computer Architecture News 44, no. 3 (2016): 329–40. http://dx.doi.org/10.1145/3007787.3001172.

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2

Jeon, Gwang Gil. "Optimal Bit Plane Arrangement for Image Size-Performance Tradeoff." Advanced Materials Research 705 (June 2013): 327–31. http://dx.doi.org/10.4028/www.scientific.net/amr.705.327.

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Анотація:

This paper discusses the issue of tradeoff between image size and performance in PSNR on bit plane image. A bit plane of a digital discrete signal is a set of bits indicate a presented bit plane in each of the binary numbers depicting the image. Image can be converted into a series of binary signal by shattering them up into their bit planes. The 0thbit plane is the least significant bit and the last bit plane is the most significant bit. Experimental results show that the best tradeoff is using the third to the seventh bit planes.

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3

Ratan, Ram, and Arvind Yadav. "Security Analysis of Bit plane Level Image Encryption Schemes." Defence Science Journal 71, no. 2 (2021): 209–21. http://dx.doi.org/10.14429/dsj.71.15643.

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A selective bit-plane encryption scheme was proposed for securing the transmission of image data in mobile environments with a claim that it provides a high security viz. the encryption of the four most significant bit-planes is sufficient for a high image data security. This paper presents the security analysis of the said encryption scheme and reports new important results. We perform the security analysis of the bit-level encryption by considering the normal images and their histogram equalised enhanced images. We consider different bit-plane aspects to analyse the security of the image enc

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4

Jeon, Gwanggil. "Performance Aware Bit Plane Allocation." International Journal of Hybrid Information Technology 9, no. 7 (2016): 139–50. http://dx.doi.org/10.14257/ijhit.2016.9.7.14.

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5

Hidayat, Rahmad. "KLASIFIKASI BIT-PLANE NOISE PADA GAMBAR MENGGUNAKAN LOGIKA FUZZY." Jurnal Ecotipe (Electronic, Control, Telecommunication, Information, and Power Engineering) 2, no. 1 (2015): 20–25. http://dx.doi.org/10.33019/ecotipe.v2i1.56.

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Teknik steganografi BPCS (Bit-Plane Complexity Segmentation) merupakan salah satu teknik steganografi yang cukup baru. Salah satu proses penting dalam Teknik Steganografi BPCS adalah proses penghitungan nilai kompleksitas suatu bit-plane. Nilai kompleksitas dihitung dengan melihat seberapa banyak pergantian bit yang terdapat dalam sebuah bit-plane. Jika bit-plane tersebut memiliki nilai kompleksitas yang tinggi, maka bi-plane tersebut dikategorikan sebagai bit-plane noise yang tidak mengandung informasi yang berharga pada gambar. Klasifikasi bit-plane yang menggunakan himpunan cripst (noise da

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6

Gu, Jun, Feng Xu, Tao Zeng, and Xin Lyu. "An Image Encryption Scheme based on Adaptive Bit-Plane Division." Journal of Physics: Conference Series 2320, no. 1 (2022): 012024. http://dx.doi.org/10.1088/1742-6596/2320/1/012024.

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Abstract With the application and popularization of digital images, the security of images has been paid more and more attention. The bit-level image encryption method has become one of the commonly used methods. It has the characteristic of changing the pixel value while disturbing the position of the pixel point, but at the same time it is accompanied by a higher computational complexity. In order to improve the efficiency of the encryption algorithm, according to the characteristic that the higher 4 of the 8 bit-planes of the grayscale image contain 94.125% of the information of the entire

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7

Choy, Siukai, Tszching Ng, Carisa Yu, and Benson Lam. "Fuzzy Bit-Plane-Dependence Region Competition." Mathematics 9, no. 19 (2021): 2392. http://dx.doi.org/10.3390/math9192392.

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This paper presents a novel variational model based on fuzzy region competition and statistical image variation modeling for image segmentation. In the energy functional of the proposed model, each region is characterized by the pixel-level color feature and region-level spatial/frequency information extracted from various image domains, which are modeled by the windowed bit-plane-dependence probability models. To efficiently minimize the energy functional, we apply an alternating minimization procedure with the use of Chambolle’s fast duality projection algorithm, where the closed-form soluti

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8

PATCHOO, Wisarn, and Thomas R. FISCHER. "Bit-Plane Coding of Lattice Codevectors." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E96.A, no. 8 (2013): 1817–20. http://dx.doi.org/10.1587/transfun.e96.a.1817.

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9

Jeon, Gwanggil. "Watermarking Application Using Bit Plane Allocation." International Journal of Security and Its Applications 8, no. 5 (2014): 139–48. http://dx.doi.org/10.14257/ijsia.2014.8.5.14.

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10

Wu, Yung-Gi. "Block truncation image bit plane coding." Optical Engineering 41, no. 10 (2002): 2476. http://dx.doi.org/10.1117/1.1503345.

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11

Choy, S. K., Kevin Yuen, and Carisa Yu. "Fuzzy bit-plane-dependence image segmentation." Signal Processing 154 (January 2019): 30–44. http://dx.doi.org/10.1016/j.sigpro.2018.08.010.

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12

Lovisolo, L., and E. A. B. da Silva. "Codebooks for vector bit-plane encoding." Electronics Letters 36, no. 12 (2000): 1038. http://dx.doi.org/10.1049/el:20000737.

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13

Wang, Chuen-Ching, and Bo-Yu Chen. "Video compression by bit-plane watermarking." International Journal of Imaging Systems and Technology 18, no. 4 (2008): 257–64. http://dx.doi.org/10.1002/ima.20134.

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14

Zhu, Hai Yan, Qing You Liu, Xiao Hua Xiao, Jia Jia Jing, and Chao He. "A 3D FEM Methodology for Air Hammer Bit Design." Advanced Materials Research 156-157 (October 2010): 1435–39. http://dx.doi.org/10.4028/www.scientific.net/amr.156-157.1435.

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Based on the failure mode of air hammer bit, a mechanical model of the tooth on the inclined plane is established. And then a new air hammer flat bit with double declined planes and a big central plat (the outer inclined plane is 40° and the inner one is 20°) is designed. In order to reduce the design cost and cut down the design cycle, we establish a 3D contact model of 12 1/4″ full-scale flat bit, teeth and rock to choose a better end face structure from single and double declined planes, verify the rationality of bit parameters and tooth arrangement, design reasonable shrink range between t

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15

Liu, Ya-Li, Tao Liu, Bin Yan, Jeng-Shyang Pan, and Hong-Mei Yang. "Visual Cryptography Using Computation-Free Bit-Plane Reconstruction." Security and Communication Networks 2022 (June 26, 2022): 1–14. http://dx.doi.org/10.1155/2022/4617885.

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Анотація:

Visual cryptography (VC) using bit-plane decomposition improves the quality of the reconstructed image. The disadvantage of this scheme is that the decoder needs computation in order to reconstruct the secret image from its bit-planes. To solve this problem, we propose a no-computation bit-plane decomposition visual cryptography (NC-BPDVC). In NC-BPDVC, we convert the grayscale secret image into a multitone image by multilevel halftoning. Then, by exploring the difference between a digital pixel and a printed dot, we design different dot patterns to render a digital pixel. By doing so, we aban

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16

Sai, N. S. T., and R. C. Patil. "Image Retrieval using Bit-plane Pixel Distribution." International Journal of Computer Science and Information Technology 3, no. 3 (2011): 159–74. http://dx.doi.org/10.5121/ijcsit.2011.3311.

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17

Kim, Kyung Yong. "Bit-plane-based lossless depth-map coding." Optical Engineering 49, no. 6 (2010): 067403. http://dx.doi.org/10.1117/1.3457668.

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18

Chengyu, Wang, and Yan Limin. "P‐4.5: A video data compression algorithm based on bit plane." SID Symposium Digest of Technical Papers 54, S1 (2023): 639–43. http://dx.doi.org/10.1002/sdtp.16373.

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High resolution and high refresh rate increase the pressure of wide transmission. Usually, video compression is used to solve this problem. However, traditional video compression methods cannot be performed in bit‐plane, which will increase the cost of storage area. For this reason, this paper first introduces a bit just noticeable difference (BJND) model based on bit‐plane. By analyzing the relationship between the bit‐plane, frequency and eccentricity, the bit just noticeable difference threshold of viewpoint is calculated. Finally, the just noticeable difference model applied to bit‐plane i

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19

Kumar, Thota Vinay, Garlapati Charanreddy, and Pulgan Lokanadh Reddy. "Low Bit Rate Image Compression Using Filtering, Bit-Plane Coding And Prefiltering." IOSR Journal of Electronics and Communication Engineering 11, no. 05 (2016): 91–96. http://dx.doi.org/10.9790/2834-1105019196.

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20

Wang, Yiding, Heng Cao, Xiaochen Jiang, and Yuanyan Tang. "Recognition of Dorsal Hand Vein Based Bit Planes and Block Mutual Information." Sensors 19, no. 17 (2019): 3718. http://dx.doi.org/10.3390/s19173718.

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The dorsal hand vein images captured by cross-device may have great differences in brightness, displacement, rotation angle and size. These deviations must influence greatly the results of dorsal hand vein recognition. To solve these problems, the method of dorsal hand vein recognition was put forward based on bit plane and block mutual information in this paper. Firstly, the input gray image of dorsal hand vein was converted to eight-bit planes to overcome the interference of brightness inside the higher bit planes and the interference of noise inside the lower bit planes. Secondly, the textu

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21

Yan, Gao, Yan Liang, Xin Zhou, and Chun Xia Qi. "A Digital Watermarking Algorithm Based on the Wavelet Bit Plane Coding." Advanced Materials Research 821-822 (September 2013): 1438–41. http://dx.doi.org/10.4028/www.scientific.net/amr.821-822.1438.

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In this paper a algorithm of digital image watermark based on wavelet bit plane is introduced, and the original image is not required for detecting the watermarking. The digital watermark is embedded by changing information of some bit planes in DWT images at different resolutions. The watermark can be extracted on the difference bit plane values of subimages of the decomposed watermarked image which is then mapped to an image with a few shades of gray. Experimental results show that the watermark is robust to several signal processing techniques, including JPEG compression and some image proc

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22

M, Ganavi, Prabhudeva S, and Hemanth Kumar N P. "An Efficient Image Steganography Scheme Using Bit-plane Slicing with Elliptic Curve Cryptography and Wavelet Transform." International Journal of Computer Network and Information Security 14, no. 4 (2022): 43–59. http://dx.doi.org/10.5815/ijcnis.2022.04.04.

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Information security is indispensable in the transmission of multimedia data. While accumulating and distributing such multimedia data, the access of data from a third person is the real security challenging issue. Information hiding plays an important role. Scramble the data before hiding it in carrier media gives enhanced security level for the data. In this paper, bit plane slicing is used to represent an input image with eight planes at bit-level instead of pixel-level. As the least significant bit contains noisy information, only the most significant bit plane can be used to represent an

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23

Chandra Sekhar, M., S. K. Chandini, V. Sai Rohith, V. Jhansi Lakshmi, and M. Pavan Kumar. "Data hiding using bit plane complexity segmentation steganography." International Journal of Engineering & Technology 7, no. 2.20 (2018): 33. http://dx.doi.org/10.14419/ijet.v7i2.20.11740.

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Steganography is the basis of information covering the puzzle in some other data (we call it the ship), leaving no obvious evidence of data change. Most conventional steganographic strategies is limited data that hide the limit. They can cover up just 10% (or less) of the information measures of the vessel. This is on the grounds that the standard of those procedures was either to supplant an uncommon piece of the recurrence parts of the vessel picture, or to supplant all the slightest critical image bits with a secret multi-valued data. Our new Steganography uses the image as vessel informati

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24

Ma, Xiaopu, Changwang Liu, and Li Zhao. "Face Fusion Recognition Based on Bit-Plane Image." Open Automation and Control Systems Journal 7, no. 1 (2015): 835–41. http://dx.doi.org/10.2174/1874444301507010835.

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25

BUI, Cong-Nguyen, Hae-Yeoun LEE, Jeong-Chun JOO, and Heung-Kyu LEE. "Secure Bit-Plane Based Steganography for Secret Communication." IEICE Transactions on Information and Systems E93-D, no. 1 (2010): 79–86. http://dx.doi.org/10.1587/transinf.e93.d.79.

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26

Kumar, Aditya, and Pardeep Singh. "Aggrandize Bit Plane Coding using Gray Code Method." International Journal of Computer Applications 20, no. 6 (2011): 44–49. http://dx.doi.org/10.5120/2434-3273.

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27

HU, Can-bin, Fang LIU, and Jun-hong ZHOU. "SAR images screening based on bit-plane characteristic." Journal of Computer Applications 29, no. 11 (2009): 3021–26. http://dx.doi.org/10.3724/sp.j.1087.2009.03021.

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28

Kim, Kyung-Yong, Gwang-Hoon Park, and Doug-Young Suh. "Bit-plane based Lossless Depth Map Coding Method." Journal of Broadcast Engineering 14, no. 5 (2009): 551–60. http://dx.doi.org/10.5909/jbe.2009.14.5.551.

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29

Li, T., S. Rahardja, and S. N. Koh. "Perceptually adaptive bit-plane coding for scalable audio." Electronics Letters 43, no. 1 (2007): 60. http://dx.doi.org/10.1049/el:20072642.

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30

Siahaan, Andysah Putera Utama. "Vernam Conjugated Manipulation of Bit-plane Complexity Segmentation." International Journal of Security and Its Applications 11, no. 9 (2017): 1–12. http://dx.doi.org/10.14257/ijsia.2017.11.9.01.

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31

Zhao, Jie, Bin Feng Yang, and Xiao Yun Wu. "Zero Watermarking Method Based on Enhanced Bit-Plane." Advanced Materials Research 989-994 (July 2014): 1473–76. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.1473.

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Анотація:

Traditional watermark embedding introduces inevitably some perceptible quality degradation of the host image. Another problem is the inherent conflict between imperceptibility and robustness. However, the zero-watermarking technique can extract some essential characteristics from the host image and use them for watermark registration and detection. The original image was decomposed into series of multiscale and directional subimages after lifting wavelet transformation (LWT). The high order bit-plane of low-frequency subimage and watermark image are inputs of the cellular neural network (CNN),

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32

Kaljahi, Maryam Asadzadeh, Palaiahnakote Shivakumara, Saqib Hakak, Mohd Yamani Idna Idris, Mohammad Hossein Anisi, and Deepu Rajan. "Saliency-based bit plane detection for network applications." Multimedia Tools and Applications 79, no. 25-26 (2020): 18495–513. http://dx.doi.org/10.1007/s11042-020-08741-9.

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33

Zhou, Ri-Gui, Ya-Juan Sun, and Ping Fan. "Quantum image Gray-code and bit-plane scrambling." Quantum Information Processing 14, no. 5 (2015): 1717–34. http://dx.doi.org/10.1007/s11128-015-0964-6.

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34

Lin, Huei-Yung, and Pin-Zhi Lin. "Hierarchical stereo matching with image bit-plane slicing." Machine Vision and Applications 24, no. 5 (2012): 883–98. http://dx.doi.org/10.1007/s00138-012-0452-2.

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35

Qian, Ziqiang, and Fu Li. "Improvements to bit-plane based image compression algorithms." Electronics Letters 34, no. 18 (1998): 1736. http://dx.doi.org/10.1049/el:19981270.

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36

Chang, Ching-Chun, Xu Wang, Ji-Hwei Horng, and Isao Echizen. "Progressive Transmission of Medical Images via a Bank of Generative Adversarial Networks." Journal of Healthcare Engineering 2021 (April 28, 2021): 1–13. http://dx.doi.org/10.1155/2021/9917545.

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Анотація:

The healthcare sector is currently undergoing a major transformation due to the recent advances in deep learning and artificial intelligence. Despite a significant breakthrough in medical imaging and diagnosis, there are still many open issues and undeveloped applications in the healthcare domain. In particular, transmission of a large volume of medical images proves to be a challenging and time-consuming problem, and yet no prior studies have investigated the use of deep neural networks towards this task. The purpose of this paper is to introduce and develop a deep-learning approach for the e

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37

V., M. Manikandan, and Masilamani V. "A Novel Bit-plane Compression based Reversible Data Hiding Scheme with Arnold Transform." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 5 (2020): 417–23. https://doi.org/10.35940/ijeat.D7008.069520.

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Reversible data hiding (RDH) is an active research area in the field of information security. The RDH scheme allows the transmission of a secret message by embedding it into a cover image, and the receiver can recover the original cover image along with the extraction of the secret message. In this paper, we propose a bit plane compression based RDH scheme to hide a sequence of secret message bits into a grayscale image. In the proposed method, a selected bit plane of the cover image will be compressed using run-length encoding (RLE) scheme. Further, the RLE sequence has been efficiently encod

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38

Ganesh, R., and S. Thabasu Kannan. "A Capable System for Hiding Image in an Image." Asian Journal of Engineering and Applied Technology 6, no. 2 (2017): 14–17. http://dx.doi.org/10.51983/ajeat-2017.6.2.822.

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In this paper, we have proposed a new method by for hiding an image using steganographic called GanKan. This method is based on Least Significant Bit (LSB) replacement and can be used for 24 bit color image capable of producing a secret-embedded image. This paper clearly showed that this GanKan new method is better than LSB technique for 8 bit color image and 24 bit color image. Firstly LSB method for both 8 bit and 24 bit color image are described and then the GanKan method for 24 bit color image, compare their result by calculating Peak Signal-to-Noise Ratio (PSNR), Mean Squared Error (MSE),

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39

B S, Lokesh, and Dr Manjunatha M B. "Thermal Image Encryption Based on Region of Interest (ROI) and Chaotic map." International Journal of Engineering & Technology 7, no. 3 (2018): 1944. http://dx.doi.org/10.14419/ijet.v7i3.15878.

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Most of the thermal image information concentrated on a particular region and 50% of image information stored in Most Significant Bit (MSB) plane. Based on these two strategy, proposed an thermal image encryption based on region of interest (ROI) and chaotic map. Firstly extract the MSB bit plane of thermal input image. This MSB bit plane undergo ROI calculation method. This method involves the partition of MSB bit plane into several 16*16 blocks. Apply the thresholding function to each block to separate the ROI blocks. Then selected part from input thermal image undergo XOR operation between

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40

Abdulmajeed, Ansam Osamah, and Sundus Abdulmuttalib Mohamed. "DFT-Based Reversible Watermarking Method for Image Ownership Protection." Pertanika Journal of Science and Technology 30, no. 3 (2022): 1883–908. http://dx.doi.org/10.47836/pjst.30.3.07.

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Анотація:

The Performance of Discrete Fourier Transform (DFT)-based watermarking methods has been carefully examined in the literature. Although the watermark in most of the literature was embedded in the DFT magnitudes using bit plane embedding, it was recently embedded in the Direct Current (DC) coefficient in the spatial domain. However, data loss due to rounding and replacement operations are still evident. Therefore, the objective of the method proposed here was to combine previous literature designs to implement a reversible DFT-based watermarking method for image ownership protection using bit pl

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41

Rangkuti, Ira Sarifah, and Edward Robinson Siagian. "Implementasi Penyembunyian Pesan Pada Audio Dengan Metode Bit-Plane Complexity Segmentation (BPCS)." JURIKOM (Jurnal Riset Komputer) 7, no. 2 (2020): 285. http://dx.doi.org/10.30865/jurikom.v7i2.2088.

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Cryptography is the science used to maintain the confidentiality of messages, by scrambling messages that are illegible. However, the results of randomization can raise suspicions that confidential communications are being carried out. Steganography can be used to overcome these problems. The trick is the message is inserted in the audio file by the Bit-Plane method. then add a message behind the file. To prevent messages from being read, the message is encrypted first with the Bit-Plane method before inserting. Application design results can be used to hide secret messages that have been encr

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42

Sadiq, B. J. S., V. Yu Tsviatkou та М. N. Bobov. "Аdaptive combined image coding with prediction of arithmetic code volume". Doklady BGUIR 19, № 2 (2021): 31–39. http://dx.doi.org/10.35596/1729-7648-2021-19-2-31-39.

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The problem of increasing the efficiency of coding of halftone images in the space of bit planes of differences in pixel values obtained using differential coding (DPCM – Differential pulse-code modulation) is considered. For a compact representation of DPCM pixel values, it is proposed to use a combined compression encoder that implements arithmetic coding and run-length coding. An arithmetic encoder provides high compression ratios, but has high computational complexity and significant encoding overhead. This makes it effective primarily for compressing the mean-value bit-planes of DPCM pixe

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43

Wang, Xingyuan, Hongyu Zhao, Yutao Hou, Chao Luo, Yingqian Zhang, and Chunpeng Wang. "Chaotic image encryption algorithm based on pseudo-random bit sequence and DNA plane." Modern Physics Letters B 33, no. 22 (2019): 1950263. http://dx.doi.org/10.1142/s0217984919502634.

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In this paper, a new chaotic image encryption algorithm based on pseudo-random bit sequence and DNA plane is proposed. The coupled map lattice (CML) is applied to design a pseudo-random bit sequence generation (PBSG) system and use the system to generate the random sequence needed in the encryption process. The initial values and parameters of the system are generated by the SHA-256 hash algorithm combined with given keys. Firstly, the plane image is decomposed into four DNA planes in combination with the DNA encoding rules, and then the four DNA planes are subjected to row circular permutatio

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44

Huang, Li, Cong Ding, Zhenjie Bao, Haitao Chen, and Changsheng Wan. "A DNA Encoding Image Encryption Algorithm Based on Chaos." Mathematics 13, no. 8 (2025): 1330. https://doi.org/10.3390/math13081330.

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With the development of society and the Internet, images have become an important medium for information exchange. To improve the security of image encryption and transmission, a new image encryption algorithm based on bit-plane decomposition, DNA encoding and the 5D Hamiltonian conservative chaotic system is proposed. This encryption scheme is different from the traditional scrambling and diffusion methods at the level of image spatial pixels but encodes images into DNA strands and completely scrambles and diffuses operations on the DNA strands to ensure the security of images and improve the

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Barannik, Vladimir, Yuriy Ryabukha, Pavlo Gurzhiy, Vitaliy Tverdokhlib, and Igor Shevchenko. "TRANSFORMANTS BIT REPRESENTATION ENCODING WITHIN VIDEO BIT RATE CONTROL." Information systems and technologies security, no. 1 (1) (2019): 52–56. http://dx.doi.org/10.17721/ists.2019.1.52-56.

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The conceptual basements of constructing an effective encoding method within the bit rate control module of video traffic in the video data processing system at the source level are considered. The essence of using the proposed method in the course of the video stream bit rate controlling disclosed, namely, the principles of constructing the fragment of the frame code representation and approaches for determining the structural units of the individual video frame within which the control is performed. The method focuses on processing the bit representation of the DCT transformants, and at his

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ISHAQ, WAQAR, ELIYA BUYUKKAYA, MUSHTAQ ALI, and ZAKIR KHAN. "VCC-BPS: Vertical Collaborative Clustering using Bit Plane Slicing." PLOS ONE 16, no. 1 (2021): e0244691. http://dx.doi.org/10.1371/journal.pone.0244691.

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The vertical collaborative clustering aims to unravel the hidden structure of data (similarity) among different sites, which will help data owners to make a smart decision without sharing actual data. For example, various hospitals located in different regions want to investigate the structure of common disease among people of different populations to identify latent causes without sharing actual data with other hospitals. Similarly, a chain of regional educational institutions wants to evaluate their students’ performance belonging to different regions based on common latent constructs. The a

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Rizzi, Maria, and Cataldo Guaragnella. "Skin Lesion Segmentation Using Image Bit-Plane Multilayer Approach." Applied Sciences 10, no. 9 (2020): 3045. http://dx.doi.org/10.3390/app10093045.

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The establishment of automatic diagnostic systems able to detect and classify skin lesions at the initial stage are getting really relevant and effective in providing support for medical personnel during clinical assessment. Image segmentation has a determinant part in computer-aided skin lesion diagnosis pipeline because it makes possible to extract and highlight information on lesion contour texture as, for example, skewness and area unevenness. However, artifacts, low contrast, indistinct boundaries, and different shapes and areas contribute to make skin lesion segmentation a challenging ta

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Sung-Jea Ko, Sung-Hee Lee, and Kyung-Hoon Lee. "Digital image stabilizing algorithms based on bit-plane matching." IEEE Transactions on Consumer Electronics 44, no. 3 (1998): 617–22. http://dx.doi.org/10.1109/30.713172.

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Ramana Rao, Y. V., and C. Eswaran. "A new algorithm for BTC image bit plane coding." IEEE Transactions on Communications 43, no. 6 (1995): 2010–11. http://dx.doi.org/10.1109/26.387439.

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Lu, T. T., and P. C. Chang. "Significant bit-plane clustering technique for JPEG2000 image coding." Electronics Letters 40, no. 17 (2004): 1056. http://dx.doi.org/10.1049/el:20045079.

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