Due to the speckle effect of coherent imaging the detection of lines in Synthetic Aperture Radar (SAR) scenes is considerably more difficult than in optical images. A new approach to detect lines in noisy images using a Markov random field (MRF) model and Bayesian classification is proposed. The unobservable object classes of single pixels are assumed to fulfill the Markov condition, i.e. to de...

Visual media data such as an image is the raw data representation for many important applications, such as image retrieval (Mikolajczyk & Schmid 2001), video classification (Lin & Hauptmann, 2002), facial expression recognition (Wang & Ahuja 2003), face recognition (Zhao, Chellappa, Phillips & Rosenfeld 2003), etc. Reducing the dimensionality of raw visual media data is highly desirable since h...

Outdoor scene parsing models are often trained on ideal datasets and produce quality results. However, this leads to a discrepancy when applied to the real world. The quality of scene parsing, particularly sky classification, decreases in night time images, images involving varying weather conditions, and scene changes due to seasonal weather. This project focuses on approaching these challenge...

In this paper we present a neuro-fuzzy approach for classification of image pixels into three classes: contour, regular or texture points. Exploiting the processing capabilities of a neural network, fuzzy classification rules are derived by learning from data and applied to classify pixels in grey-level images. To derive a proper set of training data, the spatial properties of the image feature...

This paper describes Just-In-Time Pixels, a technique for generating computer graphic images which are consistent with the sequential nature of common display devices. Motivation for Just-InTime Pixels is given in terms of an analysis of the sampling errors which will occur if the temporal characteristics of the raster scanned display are ignored. Included in the paper is a discussion of Just-I...

This paper presents a pixel-by-pixel spatial prediction method for lossless intra coding within High Efficiency Video Coding (HEVC). A well-known previous pixel-by-pixel spatial prediction method uses only two neighboring pixels for prediction, based on the angular projection idea borrowed from block-based intra prediction in lossy coding. This paper explores a method which uses three neighbori...

This paper presents one simple and novel technique for removal of impulse noise from corrupted image data. The algorithm involves impulse detection followed by spatial filtering of the corrupted pixels. In this method the presence of impulse noise is detected by a simpler method called a fuzzy logic based technique (FLT). However, the filtering idea is to recover the healthy pixel by the help o...

Introduction: Successful water and fat separation in a Dixon technique [1] requires reliable and consistent correction of phase errors that are caused by the magnetic field inhomogeneity. Among different phase correction algorithms that have been published, region growing does not require a priori assumption on the spatial distribution of the field inhomogeneity and has been successful in many ...

This paper presents a method for segmenting objects of a specific class in a given detection window. The task is to label each pixel as belonging to the foreground or the background. We pose the problem as that of finding the maximum a posterior (MAP) estimation in a modified form of Conditional Random Field model that we call a Nonparametric Inhomogeneous CRF (NICRFs). An NICRF, like a convent...

Steganography is the field of hiding messages in apparently innocuous media (e.g. images). Hiding messages in the content of images is a popular approach but since most schemes do not consider the image content when choosing the message carrying pixels, they are readily defeated by visual and statistical attacks. We show how to distribute the message in selective parts of an image (the places w...