웨이브렛 패킷 변환의 특성을 이용한 영상 암호화 알고리즘

Encryption of digital images has been requested various fields. In the meantime, many algorithms based on a text - based encryption algorithm have been proposed. In this paper, we propose a method of encryption in wavelet transform domain to utilize the characteristics of digital image. In particula...

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Published in(사)디지털산업정보학회 논문지, 14(2) Vol. 14; no. 2; pp. 49 - 59
Main Authors 신종홍, Shin, Jonghong
Format Journal Article
LanguageKorean
Published (사)디지털산업정보학회 01.06.2018
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Online AccessGet full text
ISSN1738-6667
2713-9018
DOI10.17662/ksdim.2018.14.2.049

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Summary:Encryption of digital images has been requested various fields. In the meantime, many algorithms based on a text - based encryption algorithm have been proposed. In this paper, we propose a method of encryption in wavelet transform domain to utilize the characteristics of digital image. In particular, wavelet transform is used to reduce the association between the encrypted image and the original image. Wavelet packet transformations can be decomposed into more subband images than wavelet transform, and various position permutation, numerical transformation, and visual transformation are performed on the coefficients of this subband image. As a result, this paper proposes a method that satisfies the characteristics of high encryption strength than the conventional wavelet transform and reversibility. This method also satisfies the lossless symmetric key encryption and decryption algorithm. The performance of the proposed method is confirmed by visual and quantitative. Experimental results show that the visually encrypted image is seen as a completely different signal from the original image. We also confirmed that the proposed method shows lower values of cross correlation than conventional wavelet transform. And PSNR has a sufficiently high value in terms of decoding performance of the proposed method. In this paper, we also proposed that the degree of correlation of the encrypted image can be controlled by adjusting the number of wavelet transform steps according to the characteristics of the image.
Bibliography:KISTI1.1003/JNL.JAKO201819757620975
ISSN:1738-6667
2713-9018
DOI:10.17662/ksdim.2018.14.2.049