We consider kernel density estimation when the observations are contaminated by measurement errors. It is well known that the success of kernel estimators depends heavily on the choice of a smoothing parameter called the bandwidth. A number of data-driven bandwidth selectors exist in the literature, but they are all global. Such techniques are appropriate when the density is relatively simple, ...

Today's technology allows butting a few sensor arrays to a high precision in order to capture a twodimensional image of large area. The most serious defect caused by this butting technique is the gap between sub-arrays. This paper proposes an image restoration method to recover the missing data using the information of blur. We claim that by making a reasonable assumption that the blur in real ...

We present an extended Mumford-Shah regularization for blind image deconvolution and segmentation in the context of Bayesian estimation for blurred, noisy images or video sequences. The MumfordShah functional is extended to have cost terms for the estimation of blur kernels via a newly introduced prior solution space. This functional is minimized using Γ -convergence approximation in an embedde...

In this paper, the impact of display on quality assessment is addressed. Subjective quality assessment experiments have been performed on both LCD and CRT displays. Two sets of still images and two sets of moving pictures have been assessed using either an ACR or a SAMVIQ protocol. Altogether, eight experiments have been led. Results are presented and discussed, some differences are pointed out...

Chromatic aberration distortions such as wavelength-dependent blur are caused by imperfections in photographic lenses. These distortions are much more severe in the case of color and near-infrared joint acquisition, as a wider band of wavelengths is captured. In this paper, we consider a scenario where the color image is in focus, and the NIR image captured with the same lens and same focus set...

It remains a challenge to simultaneously remove geometric distortion and space-time-varying blur in frames captured through a turbulent atmospheric medium. To solve, or at least reduce these effects, we propose a new scheme to recover a latent image from observed frames by integrating a new variational model and distortion-driven spatialtemporal kernel regression. The proposed scheme first cons...

Blur detection is affected by retinal eccentricity, but is it also affected by attentional resources? Research showing effects of selective attention on acuity and contrast sensitivity suggests that allocating attention should increase blur detection. However, research showing that blur affects selection of saccade targets suggests that blur detection may be pre-attentive. To investigate this q...

The goal of single image deblurring is to recover both a latent clear image and an underlying blur kernel from one input blurred image. Recent works focus on exploiting natural image priors or additional image observations for deblurring, but pay less attention to the influence of image structures on estimating blur kernels. What is the useful image structure and how can one select good regions...

We introduce a general method to prove uniform in bandwidth consistency of kernel-type function estimators. Examples include the kernel density estimator, the Nadaraya–Watson regression estimator and the conditional empirical process. Our results may be useful to establish uniform consistency of data-driven bandwidth kernel-type function estimators.

To build a robust visual tracking method it is important to consider issues such as low observation resolution and variation in the target object’s shape. When we capture an object moving fast in a video camera motion blur is observed. This paper introduces a visual trajectory estimation method using blur characteristics in the 3D space. We acquire a movement speed vector based on the shape of ...