one of the most fundamental features of digital image and the basic steps in image processing, analysis, pattern recognition and computer vision is the edge of an image where the preciseness and reliability of its results will affect directly on the comprehension machine system made objective world. several edge detectors have been developed in the past decades, although no single edge detector...

texture image analysis is one of the most important working realms of imageprocessing in medical sciences and industry. up to present, different approacheshave been proposed for segmentation of texture images. in this paper, we offeredunsupervised texture image segmentation based on markov random field (mrf)model. first, we used gabor filter with different parameters’ (frequency,orientation) va...

S. Krueger, T. Schaeffter, S. Weiss, K. Nehrke, T. Rozijn, P. Boernert Philips Research, Hamburg, Germany, Philips Medical Systems, Best, Netherlands Objective: Motion is one of the most prominent problems for many time-consuming MR imaging procedures. For instance, head motion during 3D scans or functional studies can cause image artifacts or deteriorate the spatial resolution of activation pa...

Image fusion is a method for obtaining a highly informative image by merging the relative information of an object obtained from two or more image sources of the same scene. The satellite cameras give a single band panchromatic (PAN) image with high spatial information and multispectral (MS) image with more spectral information. The problem exists today is either PAN or MS image is available fr...

0

Image segmentation is an essential and critical process in image processing and pattern recognition. In this paper we proposed a textured-based method to segment an input image into regions. In our method an entropy-based textured map of image is extracted, followed by an histogram equalization step to discriminate different regions. Then with the aim of eliminating unnecessary details and achi...