Time-Frequency Analysis.

Adaptive chirp mode pursuit: Algorithm and applications

A composite framework coupling multiple feature selection, compound prediction models and novel hybrid swarm optimizer-based synchronization optimization strategy for multi-step ahead short-term wind speed forecasting

An optimized time varying filtering based empirical mode decomposition method with grey wolf optimizer for machinery fault diagnosis

Recently, reversible information hiding (RIH) methods have drawn substantial attention in many privacy-sensitive real-time applications, such as the Internet of Things (IoT) enabled communications, electronic health care infrastructure, and military applications. The RIH methods are proven to be competent in such hyper-sensitive infrastructures where the loss of a single bit of information is not acceptable. In this paper, dual-layered based RIH method using modified least significant bit (LSB) matching has been proposed. The objective of the proposed work is to enhance the embedding efficiency (EE) using dual-layer based embedding strategy and to curtail the distortion caused to the stego-image to improve its quality. At the first layer of embedding, each pixel conceals two bits of information using the proposed modified LSB matching method to produce the intermediate pixel pair (IPP). Further, the IPP is utilized to conceal four bits of information during the next layer of embedding. Experimental study reveals that, the proposed method can embed 1,572,864 bits of secret data with peak signal-to-noise ratio (PSNR) of 47.86 dB, 48.05 dB, 46.51 dB and 48.14 dB, for the respective images. Further, the image quality assessment parameters like structural similarity (SSIM) index and universal image quality index (Q) are as good as the existing literature. Additionally, the proposed method shows excellent anti-steganalysis ability to regular and singular (RS) and pixel difference histogram (PDH) analysis.

Zhi Li

Papers

A time varying filter approach for empirical mode decomposition