Blind blur identification in video sequences becomes more important. This paper presents a new method for identifying parameters of different blur kernels and image restoration in a weighted double regularized Bayesian learning approach. A proposed prior solution space includes dominant blur point spread functions as prior candidates for Bayesian estimation. The double cost functions are adjust...

We propose a framework for depth estimation from a set of calibrated images, captured with a moving camera with varying parameters. Our framework respects the physical limits of the camera, and considers various effects such as motion parallax, defocus blur, zooming and occlusions which are often unavoidable. In fact, the stereo [1] and the depth from defocus [2] are essentially special cases i...

With the development of computational photography, single-lens camera combined with corresponding image deblurring algorithm is gradually becoming a new research direction, replacing complex modern optical imaging system such as single lens reflex (SLR) camera. For camera, Point Spread Function (PSF) estimation accuracy will directly affect restoration effect. In this paper, we designed simple-...

This article proposes an interval-valued extension of kernel density estimation. We show that the imprecision of this interval-valued estimation is highly correlated with the variance of the density estimation induced by the statistical variations of the set of observations.

This paper presents an efficient image enhancement method by fusion of two different exposure images in low-light condition. We use two degraded images with different exposures: one is a long-exposure image that preserves the brightness but contains blur and the other is a short-exposure image that contains a lot of noise but preserves object boundaries. The weight map used for image fusion wit...

This paper describes an approach to estimate the parameters of a motion blur (direction and length) directly form the observed image. The motion blur estimate can then be used in a standard nonblind deconvolution algorithm, thus yielding a blind motion deblurring scheme. The estimation criterion is based on recent results about the general spectral behavior of natural images. Experimental resul...

We present an approach to motion deblurring based on exploiting the information available in two differently exposed images of the same scene. Besides the normal-exposed image of the scene, we assume that a short exposed image is also available. Due to their different exposures the two images are degraded differently: the short exposed image is affected by noise, whereas the normal-exposed imag...