Enhanced Image Protection Using Discrete Fractional Fourier Domain and Dual Random Phase Encoding | Chapter 5 | New Horizons of Science, Technology and Culture Vol. 2

In the digital era, secure image transmission is critical for applications ranging from medical imaging to military surveillance. Encryption is one of the well-known techniques to provide security in the transmission of multimedia content over the internet and wireless networks. There is use of image in all the areas, so its security is of great concern nowadays. In this paper, we propose a novel method of image encryption using discrete fractional Fourier transform (DFrFT) using an exponential random phase mask. The proposed method employs a two-phase masking approach, where the input image is first modulated with a random phase mask in the spatial domain and subsequently transformed using the DFrFT with tunable fractional orders. A second random phase mask is applied in the fractional frequency domain to further obscure image content. This technique makes it almost impossible to retrieve the image without using both the right keys. The combination of multidimensional DFrFT and random phase modulation significantly increases the key space and sensitivity to initial conditions, making brute-force and plaintext attacks computationally infeasible. Experimental results validate the robustness of the proposed method in terms of Peak Signal-to-Noise Ratio (PSNR) of maximum 42.02 dB, keyspace analysis for security, computational complexity same as FrFT, processing time 2.8654 seconds and mean square error -1.5735 dB obtained.

 

Author(s) Details

Deepak Sharma
Department of Electronics and Communication Engineering, Jaypee University of Engineering & Technology, A.B. Road, Raghogarh, Guna-473226, India.

 

Subodh Kumar Singhal
Department of Electronics and Communication Engineering, Jaypee University of Engineering & Technology, A.B. Road, Raghogarh, Guna-473226, India.

 

Prateek Pandey
Department of Computer Science Engineering, Jaypee University of Engineering & Technology, A.B. Road, Raghogarh, Guna-473226, India.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/nhstc/v2/5655

Robust Encryption-Compression Scheme Based on Multiple Parameter Discrete Fractional Fourier Transform for JPEG 2000 | Chapter 5 | Mathematics and Computer Science: Contemporary Developments Vol. 7

The concept of Fractional Fourier transform (FRFT) was first introduced by N. Wiener in 1929, in quantum mechanics, the FRFT was recognized as a ‘transform method’ by mathematical bodies after the work of Victor Namias in 1980 in which the concept of FRFT had introduced by considering fractional power of eigenfunctions of the ordinary FT. Encryption along with compression is the process used to secure any multimedia content processing with minimum data storage and transmission. The transforms play a vital role in optimizing any encryption-compression systems. Earlier the original information in the existing security system based on the fractional Fourier transform (FRFT) is protected by only a certain order of FRFT. In this article, a novel method for an encryption-compression scheme based on multiple parameters of discrete fractional Fourier transform (DFRFT) with random phase matrices is proposed. The performance analysis and salient features of the proposed encryption-compression scheme are discussed in detail. The multiple-parameter discrete fractional Fourier transform (MPDFRFT) possesses all the desired properties of discrete fractional Fourier transform. The MPDFRFT converts to the DFRFT when all of its order parameters are the same. We exploit the properties of multiple-parameter DFRFT and propose a novel encryption-compression scheme using the double random phase in the MPDFRFT domain for encryption and compression data. The proposed scheme provides two-way options for data encryption and compression as well. The proposed scheme with MPDFRFT significantly enhances the data security along with the image quality of decompressed images compared to DFRFT and FRFT and it shows consistent performance with different images. The numerical simulations demonstrate the validity and efficiency of this scheme based on Peak signal to noise ratio (PSNR) and compression ratio (CR) and the robustness of the schemes against bruit force attack is examined.

 

Author (s) Details

 

Deepak Sharma
Electronics and Communication Engineering Department, Jaypee University of Engineering and Technology, Guna, India.

 

Manish Patidar
Electronics and Communication Engineering Department, Jaypee University of Engineering and Technology, Guna, India.

 

Please see the book here:- https://doi.org/10.9734/bpi/mcscd/v7/2789

A Novel Image Compression Technique with Multiple Parameter Discrete Fractional Fourier Transform for Satellite and Medical Imaging | Chapter 5 | Science and Technology: Developments and Applications Vol. 1

Image and video data compression refers to a process in which the amount of data used to represent image and video is reduced to meet a bit rate requirement while the quality of the reconstructed image or video satisfies a requirement for a certain application and the complexity of computation involved is affordable for the application. With the growing demand for high quality multimedia (HD) the data size has increased thus compression is the essential requirement to process and store data with smaller sizes. The Multiple Parameter Discrete Fractional Fourier Transform (MPDFRFT) is a generalization of the discrete fractional Fourier Transform and can be used for compression of high resolution images with the extra degree of freedom provided by the MPDFRFT and its different fractional orders finally decompressed image can also be recovered by avoiding noise. This paper deals with image compression based on MPDFRFT using Eigenvector decomposition algorithm. The MPDFRFT possesses all the desired properties of discrete fractional Fourier transform. The MPDFRFT converts to the DFRFT when all of its order parameters are the same. We exploit the properties of multiple-parameter DFRFT and propose a novel compression scheme for satellite and medical images more conveniently than urban, rural and natural images which require data retention and need to preserve for noise and distortion with the help of MPDFRFT parameters. In this scheme image is subdivided and MPDFRFT is applied for the subdivided image to form transformed coefficients and Inverse MPDFRFT is applied for reconstruction of original images. The proposed compression scheme with MPDFRFT significantly shows better results over fractional cosine transforms (FRCT), Fourier transforms (FT) and cosine transforms (CT). A comparison has been made between these techniques and observed that a good fidelity of decompressed image can be achieved at different fractional order parameter values of the transforms. The performance of the system was analyzed based on parameters like Peak Signal-to-Noise Ratio (PSNR), mean square error (MSE) and Compression Ratio (CR). The satellite defense image shows the maximum compressed image up to 60% with significant image quality with respect to the original image size and for medical error image shows a large decompressed size with 39% but medical error can be detected for smaller quality factor also and can be reconstructed with little larger size. The MPDFRFT provides better mean square error (MSE) and peak signal noise ratio (PSNR) for the same compression ratio (CR) as compared to FRCT, FT, cosine transform and classical lifting scheme based on wavelet, during image processing using MATLAB platform. 

 

Author (s) Details

 

Deepak Sharma
Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology, Guna, India.

 

Narendra Singh
Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology, Guna, India.

 

Jitendra Kanungo
Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology, Guna, India.

 

Jitendra Raghuwanshi
Department of Electronics and Communication Engineering, Jaypee University of Engineering and Technology, Guna, India.

 

 

Please see the book here:- https://doi.org/10.9734/bpi/stda/v1/3700