Depth-of-focus limitations introduce spatial blur in images of three-dimensional scenes. It is not clear how the visual system combines depth information derived from image blur with information from other depth cues. Stereoscopic disparity is the pre-eminent depth cue, so experiments were conducted to investigate interactions between image blur and stereoscopic disparity. Observers viewed two ...

Objective of this paper is to propose a new Deblurring method for motion blurred textual images. This technique is based on estimating the blur kernel or the Point Spread Function of the motion blur using Blind Deconvolution method. Motion blur is either due to the movement of the camera or the object at the time of image capture. The point spread function of the motion blur is governed by two ...

The major task in photography is motion blur.Taking clear photos under dim light using a hand-held camera is quite challenging. If the camera is set to a long exposure time, the image gets blurred due to camera shake. On the other hand, the image is dark and noisy if it is taken with a short exposure time but with a high camera gain. By combining information extracted from both blurred and nois...

Camera shake during exposure leads to image blur and poses an important problem in digital photography. Blind deconvolution recovers the sharp original image from a blurred image. MAP has been the most widely used deconvolution field but naive MAP methods mostly tends to favour no-blur solution. An intermediate representation of the image called unnatural representation has been found to the ma...

We have measured the relative perceptual scales for chromatic and luminance blur in dense textures comprised of color and luminance Gabors, using a modification of the method of paired comparisons. We find that the rate at which perceived blur grows with physical blur, when normalized to 1.0 for luminance, is 0.2 for red-green and 0.06 for blue-yellow blur. It is argued that the relatively seve...

Images of outdoor scenes are usually degraded under bad weather conditions, which results in a hazy image. To date, most haze removal methods based on a single image have ignored the effects of sensor blur and noise. Therefore, in this paper, a three-stage algorithm for haze removal, considering sensor blur and noise, is proposed. In the first stage, we preprocess the degraded image and elimina...

A blurry background due to shallow depth of field is often desired for photographs such as portraits, but, unfortunately, small point-and-shoot cameras do not permit enough defocus because of the small diameter of their lenses. We present an image-processing technique that increases the defocus in an image to simulate the shallow depth of field of a lens with a larger aperture. Our technique es...

In digital radiographic systems, a tradeoff exists between image resolution (or blur) and noise characteristics. An imaging system may only be superior in one image quality characteristic while being inferior to another in the other characteristic. In this work, a computer simulation model is presented that is to use mutual-information (MI) metric to examine tradeoff behavior between resolution...

The paper presents a novel method for joint blur identification and edge-driven image restoration in variational double regularized Bayesian estimation. The motivation is that the degradation of images includes not only additive, random noises but also multiplicative, spatial degradations, i.e., blur. Traditional nonlinear filtering techniques are observed in underutilization of blur identifica...