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In this paper, we propose a variational Bayesian method for Retinex to simulate and interpret how the human visual system perceives color. To construct a hierarchical Bayesian model, we use the Gibbs distributions as prior distributions for the reflectance and the illumination, and the gamma distributions for the model parameters. By assuming that the(More)
Compressive Sensing Deconvolution (CS Deconvolution) is a new challenge problem encountered in a wide variety of image processing fields. A compound variational regularization model which combined total variation and curve let-based sparsity prior is proposed to recovery blurred image from compressive measurements. We propose a novel fast algorithm using(More)
The paper ‘‘staircase effect alleviation by coupling gradient fidelity term” (Zhu Lixin and Xia Deshen, 2008 [1]) presented a nonlinear diffusion approach using a coupling gradient fidelity term. Although such approach helps to alleviate the staircase effect to some extent, the model is not sound. Moreover the physical mechanism of this model was explained(More)
This paper presents a new approach for hyperspectral image classification exploiting spectral–spatial information. Under the maximum a posteriori framework, we propose a supervised classification model which includes a spectral data fidelity term and a spatially adaptive Markov random field (MRF) prior in the hidden field. The data fidelity term adopted in(More)
Multiplicative noise removal is of momentous significance in coherent imaging systems and various image processing applications. This paper proposes a new nonconvex variational model for multiplicative noise removal under the Weberized total variation (TV) regularization framework. Then, we propose and investigate another surrogate strictly convex objective(More)
In this paper, we propose an improved variational level set approach to correct the bias and to segment the magnetic resonance (MR) images with inhomogeneous intensity. First, we use a Gaussian distribution with bias field as a local region descriptor in two-phase level set formulation for segmentation and bias field correction of the images with(More)
For the depth information of desired view is unknown, a per-pixel searching step is often inevitable in methods of inverse image warping. A novel approach is proposed in this paper called "cross-segment algorithm (CSA)". Different from other existing methods, CSA tickles the corresponding problem by solving the equations of crossed segments instead of(More)