This paper proposes a lightweight image encryption approach for medical Internet of Things (MIoT) networks using compressive sensing and modified seven-dimensional ( MSD ) hyperchaotic map. Initially, 7D map is to generate more secure complex secret keys. SHA-512 used create the initial conditi...

this paper presents a new coding method for image compression based on jpeg2000 and contourlet transform. jpeg2000 standard is a common standard that uses discrete wavelet transform (dwt) in the compression process. the main problems of dwt are failure to detect curved edges in image and its shortage representation of the ridge and furrow patterns which cause deficiency and block artifacts rema...

-To extract fine details from input bracketed images and preserve them in the final image, a novel exposure fusion method based on the nonsubsampled contourlet transform (NSCT) is presented in this paper,in which unique visual weight map is used for the detail extraction and an improved weight measurement is developed to remove the motion objects in dynamic scenes. Furthermore, a fast algorithm...

We propose a novel medical image fusion scheme based on the statistical dependencies between coefficients in the nonsubsampled contourlet transform (NSCT) domain, in which the probability density function of the NSCT coefficients is concisely fitted using generalized Gaussian density (GGD), as well as the similarity measurement of two subbands is accurately computed by Jensen-Shannon divergence...

The PET and CT fusion images, combining the anatomical and functional information, have important clinical meaning. This paper proposes a novel fusion framework based on adaptive pulse-coupled neural networks (PCNNs) in nonsubsampled contourlet transform (NSCT) domain for fusing whole-body PET and CT images. Firstly, the gradient average of each pixel is chosen as the linking strength of PCNN m...

An automated method of MR brain image segmentation is presented. A block based Expectation Maximization Algorithm is proposed for the tissue classification of MR brain images. The standard Gaussian Mixture Model is the most widely used method for MR Brain image segmentation and Expectation Maximization algorithm is used to estimate the model parameters. The Gaussian Mixture Model considers each...

In this paper, we present a novel medical image fusion method by taking the complementary advantages of two powerful image representation theories: nonsubsampled contourlet transform (NSCT) and sparse representation (SR). In our fusion algorithm, the NSCT is firstly performed on each of the pre-registered source images to obtain the lowpass and high-pass coefficients. Then, the low-pass bands a...