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Wyszukujesz frazę "compressive sensing" wg kryterium: Temat


Tytuł:
Compressed optical image encryption in the diffractive-imaging-based scheme by input plane and output plane random sampling
Autorzy:
Wan, Shujia
Gong, Qiong
Wang, Hongjuan
Ma, Shibang
Qin, Yi
Tematy:
diffractive-imaging-based encryption
compressive sensing
random sampling
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Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/2060687.pdf  Link otwiera się w nowym oknie
Opis:
The successful recovery of the plaintext in the simplified diffractive-imaging-based encryption (S-DIBE) scheme needs to record one intact axial intensity map as the ciphertext. By aid of compressive sensing, we propose here a new image encryption approach, referred to as compressed DIBE (C-DIBE), which allows further compression of the intensity map. The plaintext is sampled before being sent to DIBE. Afterwards, the intensity map recorded by the CCD camera is also processed by such sampling operation to generate the ciphertext. For decryption, we first obtain the sparse plaintext using the proposed phase retrieval algorithm, and then reobtain the primary plaintext from it via compressive sensing. Numerical results show that a proper proportion of the intensity map (e.g. 50%) is enough to totally recover a grayscale image. We achieve multiple-image encryption by space multiplexing without enlarging the size of the ciphertext. The robustness of C-DIBE against brute-force attack evidently outperforms S-DIBE due to the extended key space. Numerical simulation has been presented to confirm the proposal.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The Development of a Generative Approach for Joint Super-Resolution Image Reconstruction from Highly Sparse Raw Data in the Context of MR-PET Imaging
Autorzy:
Malczewski, Krzysztof
Tematy:
GAN
WGAN
super-resolution
compressive sensing
medical modalities
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Wydawca:
Szkoła Główna Gospodarstwa Wiejskiego w Warszawie. Instytut Informatyki Technicznej
Powiązania:
https://bibliotekanauki.pl/articles/59122867.pdf  Link otwiera się w nowym oknie
Opis:
The present study introduces a rapid and efficient approach for reconstructing high-resolution images in hybrid MRI-PET scanners. The application of sparsity, compressed sensing (CS), and super-resolution reconstruction (SRR) methodologies can significantly decrease the demands of data acquisition while concurrently attaining high-resolution output. G-guided generative multilevel networks for sparsely sampled MR-PET input are shown here. Compressed Sensing using conjugate symmetry and Partial Fourier methodology speeds up data collection over k-space sampling methods. GANs and k-space adjustments are used in this image domain technique. The employed methodology utilizes discrete preprocessing stages to effectively tackle the challenges associated with the deblurring, reducing motion artifacts, and denoising of layers. Initial trials offer contextual details and accelerate evaluations. Preliminary experiments provide contextual information and expedite assessments.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Image compression-encryption algorithm combining compressive sensing with log operation
Autorzy:
Chen, R.-L.
Zhou, Y.
Luo, M.
Zhang, A.-D.
Gong, L.-H.
Tematy:
image encryption
image compression
compressive sensing
log operation
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Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/174009.pdf  Link otwiera się w nowym oknie
Opis:
Based on compressive sensing and log operation, a new image compression-encryption algorithm is proposed, which accomplishes encryption and compression simultaneously. The proposed image compression-encryption algorithm takes advantage of not only the physical realizability of partial Hadamard matrix, but also the resistance of the chosen-plaintext attack since all the elements in the partial Hadamard matrix are 1, –1 or log 1 = 0. The proposed algorithm is sensitive to the key and it can resist various common attacks. The simulation results verify the validity and reliability of the proposed image compression-encryption algorithm.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Image compression and encryption algorithm with wavelet-transform-based 2D compressive sensing
Autorzy:
Fan, Jing-Hui
Liu, Xian-Bao
Chen, Yan-Bin
Tematy:
wavelet transform
compressive sensing
chaos scrambling
image encryption
image compression
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Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/175122.pdf  Link otwiera się w nowym oknie
Opis:
By combining a wavelet transform with chaos scrambling, an image compression and encryption algorithm based on 2D compressive sensing is designed. The wavelet transform is employed to obtain the sparse representation of a plaintext image. The sparse image is measured in two orthogonal directions by compressive sensing. Then, the result of 2D compressive sensing is confused by the Arnold transform and the random pixel scrambling. The combination of four-dimensional chaos and logistic map is exploited to generate the first row of the key-controlled circulant matrix. The proposed algorithm not only carries out image compression and encryption simultaneously, but also reduces the consumption of the key by controlling the generation of measurement matrix. Experimental results reveal that the proposed image compression and encryption algorithm is resistant to noise attacks with good compression performance and high key sensitivity.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Compressive-sensing-based double-image encryption algorithm combining double random phase encoding with Josephus traversing operation
Autorzy:
Jiang, Hao
Nie, Zhe
Zhou, Nanrun
Zhang, Wenquan
Tematy:
image encryption
compressive sensing
double random phase encoding
Josephus traversing
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Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/173461.pdf  Link otwiera się w nowym oknie
Opis:
A double-image encryption scheme based on compressive sensing is designed by combining a double random phase encoding technique with Josephus traversing operation. Two original images are first compressed and encrypted by compressive sensing in the discrete wavelet domain and then connected into a complex image according to the order of the alternate rows. Moreover, the resulting image is re-encrypted into stationary white noise by a double random phase encoding technique. Lastly, Josephus traversing method is utilized to scramble the transformed image. The initial states of the Henon chaotic map are the secret keys of this double-image encryption algorithm, which can be used to control the construction of the measurement matrix in compressive sensing and generation of the random-phase mask in double random phase encoding. Simulation results show that the proposed double-image encryption algorithm is effective and secure.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Pilot Design for Sparse Channel Estimation in Orthogonal Frequency Division Multiplexing Systems
Autorzy:
Vimala, P.
Yamuna, G.
Tematy:
channel estimation
compressive sensing
minimum coherence
minimum variance
pilot pattern
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Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Powiązania:
https://bibliotekanauki.pl/articles/309257.pdf  Link otwiera się w nowym oknie
Opis:
Orthogonal Frequency Division Multiplexing (OFDM) is a well-known technique used in modern wide band wireless communication systems. Coherent OFDM systems achieve its advantages over a multipath fading channel, if channel impulse response is estimated precisely at the receiver. Pilot-aided channel estimation in wide band OFDM systems adopts the recently explored compressive sensing technique to decrease the transmission overhead of pilot subcarriers, since it exploits the inherent sparsity of the wireless fading channel. The accuracy of compressive sensing techniques in sparse channel estimation is based on the location of pilots among OFDM subcarriers. A sufficient condition for the optimal pilot selection from Sylow subgroups is derived. A Sylow subgroup does not exist for most practical OFDM systems. Therefore, a deterministic pilot search algorithm is described to select pilot locations based on minimizing coherence, along with minimum variance. Simulation results reveal the effectiveness of the proposed algorithm in terms of bit error rate, compared to the existing solutions.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Semantic Sparse Representation of Disease Patterns
Autorzy:
Przelaskowski, A.
Tematy:
sparse representation
compressive sensing
information theory
semantic information
disease pattern
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Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Powiązania:
https://bibliotekanauki.pl/articles/226810.pdf  Link otwiera się w nowym oknie
Opis:
Sparse data representation is discussed in a context of useful fundamentals led to semantic content description and extraction of information. Disease patterns as semantic information extracted from medical images were underlined because of discussed application of computer-aided diagnosis. Compressive sensing rules were adjusted to the requirements of diagnostic pattern recognition. Proposed methodology of sparse disease patterns considers accuracy of sparse representation to estimate target content for detailed analysis. Semantics of sparse representation were modeled by morphological content analysis. Subtle or hidden components were extracted and displayed to increase information completeness. Usefulness of sparsity was verified for computer-aided diagnosis of stroke based on brain CT scans. Implemented method was based on selective and sparse representation of subtle hypodensity to improve diagnosis. Visual expression of disease signatures was fixed to radiologist requirements, domain knowledge and experimental analysis issues. Diagnosis assistance suitability was proven by experimental subjective rating and automatic recognition.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of a deep-learning neural network for image reconstruction from a single-pixel infrared camera
Autorzy:
Urbaś, Sebastian
Więcek, Bogusław
Tematy:
single-pixel imaging
compressive sensing
thermal imaging
convolutional neural network
dataset augmentation
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Wydawca:
Polska Akademia Nauk. Stowarzyszenie Elektryków Polskich
Powiązania:
https://bibliotekanauki.pl/articles/59112910.pdf  Link otwiera się w nowym oknie
Opis:
The article presents the simulation results of a single-pixel infrared camera image reconstruction obtained by using a convolutional neural network (CNN). Simulations were carried out for infrared images with a resolution of 80 × 80 pixels, generated by a low-cost, low-resolution thermal imaging camera. The study compares the reconstruction results using the CNN and the ℓ₁ reconstruction algorithm. The results obtained using the neural network confirm a better quality of the reconstructed images with the same compression rate expressed by the peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM).
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Color image encryption scheme based on quaternion discrete multi-fractional random transform and compressive sensing
Autorzy:
Ye, Huo-Sheng
Dai, Jing-Yi
Wen, Shun-Xi
Gong, Li-Hua
Zhang, Wen-Quan
Tematy:
color image encryption
quaternion discrete multi-fractional random transform
compressive sensing
confusion-diffusion strategy
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Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/2033985.pdf  Link otwiera się w nowym oknie
Opis:
A color image compression-encryption algorithm by combining quaternion discrete multi-fractional random transform with compressive sensing is investigated, in which the chaos-based fractional orders greatly improve key sensitivity. The original color image is compressed and encrypted with the assistance of compressive sensing, in which the partial Hadamard matrix adopted as a measurement matrix is constructed by iterating Chebyshev map instead of utilizing the entire Guassian matrix as a key. The sparse images are divided into 12 sub-images and then represented as three quaternion signals, which are modulated by the quaternion discrete multi-fractional random transform. The image blocking and the quaternion representation make the proposed cryptosystem avoid additional data extension existing in many transform-based methods. To further improve the level of security, the plaintext-related key streams generated by the 2D logistic-sine-coupling map are adopted to diffuse and confuse the intermediate results simultaneously. Consequently, the final ciphertext image is attained. Simulation results reveal that the proposed cryptosystem is feasible with high security and has strong robustness against various attacks.
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Multi-color-image compression-encryption scheme in the quaternion discrete Fresnel domain
Autorzy:
Hu, Ze-Ting
Zeng, Ping-Ping
Ding, Hong-Xing
Gong, Li-Hua
Chen, Su-Hua
Tematy:
compressive sensing
quaternion discrete Fresnel transform
2D-LSCM chaotic system
image compression-encryption algorithm
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Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Powiązania:
https://bibliotekanauki.pl/articles/58970442.pdf  Link otwiera się w nowym oknie
Opis:
A multiple color images compression-encryption scheme is designed with compressive sensing in the quaternion discrete Fresnel transform. To tackle multiple color images in a holistic manner, the discrete Fresnel transform is extended into the quaternion domain and the images are encrypted with the quaternion discrete Fresnel transform. In this scheme, the RGB color components of plaintext images are simultaneously compressed and encrypted in three mutually independent channels. Then the red, green and blue components are scrambled respectively by a chaos sequence generated by the 2D logistic-sine-coupling map. Each color component matrix is compressed with sparse representation and matrix measurement. Subsequently, the compressed matrices are integrated into the quaternion algebras and re-encrypted by the defined quaternion discrete Fresnel transform. The devised nonlinear cryptosystem originates from the asymmetric phase truncation operation. In decryption, the original color images are reconstructed by the gradient descent with a sparsification algorithm. The proposed multiple color images compression-encryption algorithm is feasible, effective, secure and robust.
Dostawca treści:
Biblioteka Nauki
Artykuł

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