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M.Tech / M.E / PhD Thesis | Information Technology | India | Volume 4 Issue 2, February 2015
Highly Secured Lossless Image Cryptography Algorithm Based on Haar Wavelet Transform
Rishi Kumar Gupta [8] | G. Sujatha [4]
Abstract: Along with the rapid increasing growth of computer and network technologies, images are being transmitted more and more frequently. Security of image is a big issue. Image information is lively and visual, and has been an important means of expressing information of person. There are many encryption algorithm had been available each one having some strength and weakness. Image cryptography can use text cryptosystems to encrypt images directly, since image size is greater than text. Image encryption can be classified into lossy and lossless encryption methods. Lossless encryption methods are more applicable than lossy encryption methods when marginal distortion is not tolerable. In the proposed system, find the hash value of image using by image hashing toolbox. Image hashing is very easy to the tamper with digital data without leaving any clues. Under these circumstances, integrity verification has become an important issue in the digital world. After finding the hash value, the image is transformed into the frequency domain using the wavelet transform, Image processing and analysis based on the continuous or discrete image transforms are classic techniques. The image transforms are widely used in image filtering, data description, etc. Nowadays the wavelet theorems make up very popular methods of image processing, de-noising and compression. The image transform theory is a well-known area characterized by a precise mathematical background. Considering that the Haar functions are the simplest wavelets, these forms are used in many methods of discrete image transforms and processing then the image sub-bands are encrypted in a such way that guarantees a secure, reliable, and an unbreakable form. The encryption involves scattering the distinguishable frequency data in the image using a reversible weighting factor amongst the rest of the frequencies. The algorithm is designed to shuffle and reverse the sign of each frequency in the transformed image before the image frequencies are transformed back to the pixel domain. The decryption algorithm reverses the encryption process and restores the image to its original form.
Keywords: Wavelets, Haar Transform, Lossless image encryption/decryption, Symmetric key encryption, Image hashing, Block based matrix transformation
Edition: Volume 4 Issue 2, February 2015,
Pages: 2430 - 2432