Neeru Jindal

Image and video processing using discrete fractional transforms

The mathematical transforms such as Fourier transform, wavelet transform and fractional Fourier transform have long been influential mathematical tools in information processing. These transforms process signal from time to frequency domain or in joint time–frequency domain. In this paper, with the aim to review a concise and self-reliant course, the discrete fractional transforms have been comprehensively and systematically treated from the signal processing point of view. Beginning from the definitions of fractional transforms, discrete fractional Fourier transforms, discrete fractional Cosine transforms and discrete fractional Hartley transforms, the paper discusses their applications in image and video compression and encryption. The significant features of discrete fractional transforms benefit from their extra degree of freedom that is provided by fractional orders. Comparison of performance states that discrete fractional Fourier transform is superior in compression, while discrete fractional cosine transform is better in encryption of image and video. Mean square error and peak signal-to-noise ratio with optimum fractional order are considered quality check parameters in image and video.

Image Retrieval Algorithm Based on Discrete Fractional Transforms

The discrete fractional transforms is a signal processing tool which suggests computational algorithms and solutions to various sophisticated applications. In this paper, a new technique to retrieve the encrypted and scrambled image based on discrete fractional transforms has been proposed. Two-dimensional image was encrypted using discrete fractional transforms with three fractional orders and two random phase masks placed in the two intermediate planes. The significant feature of discrete fractional transforms benefits from its extra degree of freedom that is provided by its fractional orders. Security strength was enhanced (1024!)4 times by scrambling the encrypted image. In decryption process, image retrieval is sensitive for both correct fractional order keys and scrambling algorithm. The proposed approach make the brute force attack infeasible. Mean square error and relative error are the recital parameters to verify validity of proposed method.

A secure image encryption algorithm based on fractional transforms and scrambling in combination with multimodal biometric keys

In today’s digital world, security is a preeminent element in the transmission of digital images. In this paper, image encryption algorithm is proposed using fractional transform and scrambling along with multimodal biometric keys. For unauthorized persons, it is very difficult to retrieve the biometric keys. Firstly, both iris and fingerprint binary codes are XORed and given to the original image. This randomized image is secured using fractional order as a key. The significant feature of fractional transforms benefits from its extra degree of freedom that is provided by its fractional orders. The fractional order is calculated from the iris key. To make the encryption more confusing, scrambling is used to shuffle the position of pixels. Experimental results like histogram analysis, correlation analysis, peak signal-to-noise ratio, mean square error, structural similarity index measure, spectral distortion, information entropy, key sensitivity analysis, differential attacks and spoofing attacks verify the efficacy of proposed algorithm.

Image-adaptive watermarking using maximum likelihood decoder for medical images

In this paper, a new medical image-adaptive watermarking technique is proposed in which embedding of the watermark is done in low frequency coefficients for achieving high robustness using an adjustable dynamic strength factor. The low frequency coefficients are modeled using Gaussian distribution to design a Maximum Likelihood (ML) decoder. The decoder recovers the watermark with the help of side information containing the adjustable dynamic strength factor, position of blocks (used for embedding), mean and variances of low frequency coefficients. The method contributes towards a highly flexible and easily adjustable dynamic strength factor for achieving the best imperceptibility with the highest robustness. The validity of the new technique is verified against various attacks and the results are compared with other watermarking schemes. The proposed technique is found to generate better results.

Image compression algorithm with reduced blocking artifacts

The modern communication era has led to a proliferation of digital media contents. However, the large volume of data poses difficulties because of increased bandwidth and limited storage space. Hence, this has led to the need for compression techniques. Image compression with block processing allows the coder to adapt to local image statistics and exploit the correlation present among neighboring image pixels. The main degradation factor of block transform coding is blocking artifacts (visually undesirable patterns) at high compression ratios. The degradation occurs because of coarse quantization of the transform coefficients and the independent processing of the blocks. In this paper, the novelty of the algorithm is its ability to detect and reduce the blocking artifacts using nonseparable discrete fractional Fourier transform (NSDFrFT) at high compression ratios. Three transform techniques, namely nearest neighbor interpolation, bilinear interpolation, and bicubic interpolation, were implemented. The NSDFrFT-bicubic interpolation resulted in a structurally similar high subjective quality reconstructed image with reduced blocking (for low frequency images) at high compression ratios. Simulation results are calculated with many image quality metrics such as peak signal to noise ratio, mean square error, structural similarity index, and gradient magnitude similarity measure. Evaluations, such as comparisons between the proposed and existing algorithms (DFrFT, FFT), are presented with relevant tables, graphs, and figures.