Image zooming is one of the current issues of image processing where maintaining the quality and structure of the zoomed image is important. To zoom an image, it is necessary that the extra pixels be placed in the data of the image. Adding the data to the image must be consistent with the texture in the image and not to create artificial blocks. In this study, the required pixels are estimated ...

Image identification involves estimating the properties of an imperfect imaging system from an observed image prior to the restoration process. In this paper we present a novel identification technique for multichannel image processing using the maximum likelihood estimation (ML) approach. The image is represented as an autoregressive (AR) model and blur is described as a continuous spatial dom...

Image manipulation has become commonplace in today's social context. One of the most common types of image forgeries is image compositing. In recent years, researchers have proposed various methods for detecting such splicing. Most prior approaches to detecting blur post-processing operation suffer from their inability to identify the spliced region when the background region contained nature b...

While capturing images of a scene, the relative motion between the camera and the scene during exposure leads to motion-blur in images. The convolution model for motion-blur is applicable only when the camera motion is restricted to in-plane translations. Blur arising due to rotation and out-of-plane translation of camera cannot be modeled using convolution with a single blur kernel [3, 5, 6]. ...

Digital photos are massively produced while digital cameras are becoming popular, however, not every photo has good quality. Blur is one of the conventional image quality degradation which is caused by various factors. In this paper, we propose a scheme to detect blurred images and classify them into several different categories. The blur detector uses support vector machines to estimate the bl...

Developing an objective metric, which automatically quantifies perceived image quality degradation induced by blur, is highly beneficial for current digital imaging systems. In many applications, these objective metrics need to be of the noreference (NR) type, which implies that quality prediction is based on the distorted image only. Recent progress in the development of a NR blur metric is ev...

The visual system can distinguish different levels of blur and different levels of excess sharpness. Adaptation alters this capacity so that the adapted blur (or sharp) level looks more like a normal, properly focused image. Here, we describe the more general pattern of aftereffects of blur and sharp adaptation by measuring matching functions, using video clips from a DVD movie as stimuli. Resu...

The aim of image restoration is to obtain a higher quality desired image from a degraded image. In this strategy, an image inpainting method fills the degraded or lost area of the image by appropriate information. This is performed in such a way so that the obtained image is undistinguishable for a casual person who is unfamiliar with the original image. In this paper, different images are degr...

A wide-area image can be synthesized from an image sequence taken with a moving camera by using image mosaicing techniques. However, motion blur caused by the motion of the camera may significantly degrade the quality of the synthesized image. In this paper, we propose a new method for generating a deblurred mosaic from an image sequence that is degraded by motion blur under the condition that ...