This paper proposes a separable reversible data-hiding scheme in encrypted image which offers high payload and error-free data extraction. The cover image is partitioned into nonoverlapping blocks and multigranularity encryption is applied to obtain the encrypted image. The data hider preprocesses the encrypted image and randomly selects two basic pixels in each block to estimate the block smoo...

This paper presents an adaptive regularized image interpolation algorithm from blurred and noisy low resolution image sequence, which is developed by a general framework based on data fusion. This framework can preserve edge information and suppress noise, effectively. To obtain a higher resolution image, both discontinuities across the edge orientation and smoothness along the edge orientation...

We studied two image characteristics, the smoothness and the similarity, which give rise to local and global redundancy in image representation. The smoothness means that the gray level values within a given block vary gradually rather than abruptly. The similarity means that any patterns in an image repeat itself anywhere in the rest of the image. In this sense, we proposed a lossless medical ...

Graph cut minimization formulates the image segmentation as a linear combination of problem constraints. The salient constraints of the computer vision problems are data and smoothness which are combined through a regularization parameter. The main task of the regularization parameter is to determine the weight of the smoothness constraint on the graph energy. However, the difference in functio...

During image deblocking, the preservation of visually significant edges in the image is important. Based on the observation that blocking artifact along edge direction is difficult for human perception, a number of existing techniques have proposed to filter the edge pixels with low weight or bypass them altogether to avoid blurring. However, the un-processed artifacts that are anti-parallel to...

A new cost function based on stochastic fuzzy discrimination information measure is introduced in this paper. Focusing on their significant parts, this cost function is used to find the optimal value of threshold for denoising image. It is, in fact, an extension of fuzzy entropy cost function by the present author. Multivariable normal distribution is used for creating focus on significant part...

Recently, much attention has been paid to reversible data hiding (RDH) in encrypted images, since it preserves the data that the original image can be perfectly recovered after data extraction while protecting the confidentiality of image content. In this paper, we propose joint and separable RDH techniques using an improved embedding pattern and a new measurement function in encrypted images w...

Statistical modeling of natural image sequences is of fundamental importance to both the understanding of biological visual systems and the development of Bayesian approaches for solving a wide variety of machine vision and image processing problems. Previous methods are based on measuring spatiotemporal power spectra and by optimizing the best linear filters to achieve independent or sparse re...

We presented and evaluated a new Bayesian method for range image segmentation. The method proceeds in to stages. First, an initial segmentation was produced by a randomized region growing technique. The produced segmentation was considered as a degraded version of the ideal segmentation, which should be then refined. In the second stage, image pixels not labeled in the first stage were labeled ...