Analysis and interpretation of an image which was acquired by a non ideal imaging system is the key problem in many application areas. The observed image is usually corrupted by blurring, spatial degradations, and random noise. In this paper, we propose an alternative approach. We derive the features for image representation which are invariant with respect to blur regardless of the degradation...

The objective of the present work is to evaluate the suitability of using 3D digital image correlation (DIC) for measuring strains on high-speed flywheels. A two-camera DIC setup was used to characterize the effect of image blur on de-correlation and to measure strains on the surface of three 32-cm diameter plastic disks rotating in air at low speeds (2,000 rpm). In one set of experiments, imag...

Camera shake during exposure leads to objectionable image blur and ruins many photographs. Conventional blind deconvolution methods typically assume frequency-domain constraints on images, or overly simplified parametric forms for the motion path during camera shake. Real camera motions can follow convoluted paths, and a spatial domain prior can better maintain visually salient image characteri...

A blind single-image super resolution method is proposed to enhance the spatial resolution of the image with defocus blur. Firstly, according to the low resolution imaging model, a framework of blind singleimage super resolution reconstruction is presented. Secondly, utilizing Wiener filtering algorithm, the errorparameter curve of the defocus blurred image was generated, through which the defo...

Many conventional blind image deconvolution algorithms have much processing time because the consideration of various cases and the optimization are required for general employment. Moreover, these algorithms are also complex to deal with various point spread functions (PSF). Therefore, this paper restricts the type of PSF to the dual-exposure type and proposes effective PSF search algorithm, u...

The purpose of our study is to introduce a new method for depth of field blur simulation used for compositing real and synthetic images in a realistic way. Existing methods do not simulate accurately the depth of field blur produced by photographic equipment. The problem is twofold: photometric and geometric. Existing methods based on convolution do not produce a realistic photometric rendering...

Image restoration is to improve the quality of a digital image which has been degraded due to various phenomena like blur, noise. An image with uniform motion blur and Poisson noise is considered. Images acquired at different exposure times are obtained and SNR values for each image are calculated. The blurred and noisy images are restored using the pseudo-inverse filter and SNR values are calc...

The lens system in the human eye is able to best focus light from only one distance at a time.Therefore, many objects in the natural environment are not imaged sharply on the retina. Furthermore, light from objects in the environment is subject to the particular aberrations of the observer's lens system (e.g., astigmatism and chromatic aberration). We refer to blur created by the observer's opt...

Spatial quality and spectral quality are the two important indexes that are used to evaluate the quality of any fused image. Most of the existing methods for this purpose, however, considered only the spectral quality except for that proposed by Zhou et al., while the latter cannot be used to compare directly the spatial resolution between the fused image and original high-resolution. A new spa...

This paper proposes a simple, accurate, and robust approach to single image nonparametric blind Super-Resolution (SR). This task is formulated as a functional to be minimized with respect to both an intermediate super-resolved image and a nonparametric blur-kernel. The proposed approach includes a convolution consistency constraint which uses a non-blind learning-based SR result to better guide...