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1
Image encryption based on phase encoding by means of a fringe pattern and computational algorithms
Publicado 2006Fuente: Universidad Nacional Autónoma de MéxicoTipo de material: Artículo de InvestigaciónDescripción: Resumen: A computational technique for image encryption and decryption is presented. The technique is based on light reflection, intensity superposition and computational algorithms. The image to be encrypted is a reflectance map obtained by means of the light reflected by a scene. To perform the encryption procedure, the image is encoded in a computer-generated fringe pattern. The model of the fringe pattern is a cosine function, which adds to its argument the image to be encrypted as a phase. It generates a fringe pattern deformed according to the image. To complete the encryption, a random mask is superimposed on the fringe pattern. The decryption procedure is performed by subtracting the random mask from the encrypted image and applying a phase recovery method. To retrieve the phase from the fringe pattern, the heterodyne demodulation method is used. To describe the accuracy of results of the decrypted images and the robustness of the encryption, a root mean square of error is calculated. All steps of the encryption and decryption are performed in computational form. The results of encryption and decryption are thus improved. It represents a contribution to the field of encryption and decryption. This technique is tested with simulated images and real images, and its results are presented.Acceso al recurso -
2
Solving the encoding bottleneck: of the HHL algorithm, by the HHL algorithm
Publicado 2025Fuente: arXivTipo de material: PreprintAcceso al recurso -
3
Quantum superposing algorithm for quantum encoding
Publicado 2024Fuente: arXivTipo de material: PreprintAcceso al recurso -
4
Encoding-Invariant Variance Amplification and the Failure of Encoding-Invariant Collapse: A Diagnostic Probe
Publicado 2026Fuente: ZenodoTipo de material: Recurso digitalAcceso al recurso -
5
Neural network encoded variational quantum algorithms
Publicado 2023Fuente: arXivTipo de material: PreprintAcceso al recurso -
6
Explainable quantum regression algorithm with encoded data structure
Publicado 2023Fuente: arXivTipo de material: PreprintAcceso al recurso -
7
Explainable quantum regression algorithm with encoded data structure
Publicado 2026Fuente: arXivTipo de material: PreprintAcceso al recurso -
8
A quantum algorithm for the Kalman filter using block encoding
Publicado 2024Fuente: arXivTipo de material: PreprintAcceso al recurso -
9
An optimal algorithm for estimating angular speed using incremental encoders
Publicado 2013Fuente: RedalycTipo de material: Artículo científicoAcceso al recurso -
10
Feature-based fast coding unit partition algorithm for high efficiency video coding
Publicado 2015Fuente: Universidad Nacional Autónoma de MéxicoTipo de material: Artículo de InvestigaciónDescripción: Resumen: High Efficiency Video Coding (HEVC), which is the newest video coding standard, has been developed for the efficient compression of ultra high definition videos. One of the important features in HEVC is the adoption of a quad-tree based video coding structure, in which each incoming frame is represented as a set of non-overlapped coding tree blocks (CTB) by variable-block sized prediction and coding process. To do this, each CTB needs to be recursively partitioned into coding unit (CU), predict unit (PU) and transform unit (TU) during the coding process, leading to a huge computational load in the coding of each video frame. This paper proposes to extract visual features in a CTB and uses them to simplify the coding procedure by reducing the depth of quad-tree partition for each CTB in HEVC intra coding mode. A measure for the edge strength in a CTB, which is defined with simple Sobel edge detection, is used to constrain the possible maximum depth of quad-tree partition of the CTB. With the constrained partition depth, the proposed method can reduce a lot of encoding time. Experimental results by HM10.1 show that the average time-savings is about 13.4% under the increase of encoded BD-Rate by only 0.02%, which is a less performance degradation in comparison to other similar methods. All Rights Reserved © 2015 Universidad Nacional Autónoma de México, Centro de Ciencias Aplicadas y Desarrollo Tecnológico. This is an open access item distributed under the Creative Commons CC License BY-NC-ND 4.0.Acceso al recurso -
11
Quantum sampling algorithms for quantum state preparation and matrix block-encoding
Publicado 2024Fuente: arXivTipo de material: PreprintAcceso al recurso -
12
A comparison on constrain encoding methods for quantum approximate optimization algorithm
Publicado 2024Fuente: arXivTipo de material: PreprintAcceso al recurso -
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Matrix encoding method in variational algorithm of calculating eigenvalues and generalized eigenvalues
Publicado 2026Fuente: arXivTipo de material: PreprintAcceso al recurso -
14
Approximate complex amplitude encoding algorithm and its application to data classification problems
Publicado 2022Fuente: arXivTipo de material: PreprintAcceso al recurso -
15
Variational quantum algorithm based on Lagrange polynomial encoding to solve differential equations
Publicado 2024Fuente: arXivTipo de material: PreprintAcceso al recurso -
16
S-FABLE and LS-FABLE: Fast approximate block-encoding algorithms for unstructured sparse matrices
Publicado 2024Fuente: arXivTipo de material: PreprintAcceso al recurso -
17
Image encryption based on phase encoding by means of a fringe pattern and computational algorithms
Publicado 2006Fuente: RedalycTipo de material: Artículo científicoAcceso al recurso -
18
Image encryption based on phase encoding by means of a fringe pattern and computational algorithms
Publicado 2006Fuente: RedalycTipo de material: Artículo científicoAcceso al recurso -
19
Practical Guide to Quantum Computing – Variational Algorithms: Cost Functions (Based on Materials from IBM Q) # 4
Publicado 2026Fuente: ZenodoTipo de material: Recurso digitalAcceso al recurso -
20
Vanishing performance of the parity-encoded quantum approximate optimization algorithm applied to spin-glass models
Publicado 2023Fuente: arXivTipo de material: PreprintAcceso al recurso