Double-image encryption algorithm based on discrete fractional angular transform and fractional Fourier transform

• Autorzy: Qiu Tian , Dai Wei-Hua , Chen Su-Hua , Zhou Hang , Gong Li-Hua

Identyfikatory

DOI

10.37190/oa220415

• Języki publikacji: EN

Abstrakty

EN

By combining fractional Fourier transform with discrete fractional angular transform, a double-image encryption algorithm is designed. The discrete cosine transform is performed on two grayscale images to generate a spectrum image, and then the generated spectrum image is compressed into an image with Zigzag scanning. The compressed image is processed with the discrete fractional angular transform, and then fractional Fourier transform and double random phase coding are executed on the image. The DNA operation controlled by chaotic system is introduced to change the pixel values. Finally, the ciphertext image is obtained through bit-level permutation and pixel adaptive diffusion. The statistical information of the plaintext images is employed as the input of the SHA-256 to calculate the initial conditions of the chaotic map. Simulation experiments demonstrate that the double-image encryption algorithm can effectively reduce the correlation among adjacent pixels of the plaintext images.

Słowa kluczowe

EN

chaotic system; fractional transform; discrete fractional angular transform; double-image encryption

• Wydawca: Oficyna Wydawnicza Politechniki Wrocławskiej
• Czasopismo: Optica Applicata
• Rocznik: 2022
• Tom: Vol. 52, nr 4
• Strony: 669--684
• Opis fizyczny: Bibliogr. 24 poz., rys., tab.

Twórcy

autor

Qiu Tian

• Department of Mathematics, Nanchang University, Nanchang 330031, China
• Department of Electronic Information Engineering, Nanchang University, Nanchang 330031, China

autor

Dai Wei-Hua

• School of Computer Science and Engineering, Northeastern University, Shenyang, 110169, China

autor

Chen Su-Hua

• Department of Electronic Information Engineering, Nanchang University, Nanchang 330031, China

autor

Zhou Hang

• Department of Electronic Information Engineering, Nanchang University, Nanchang 330031, China

autor

Gong Li-Hua

• Department of Electronic Information Engineering, Nanchang University, Nanchang 330031, China

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).