sar (synthetic aperture radar) image enhancement and segmentation is purpose of this thesis. sar image segmentation is a primary step before steps such as classification and target recognition. the main obstacle in sar image segmentation is inherent speckle noise. speckle noise is a multiplicative and highly destructive noise which results to intensity inhomogeneity. hence common segmentation m...

image segmentation is an important task in image processing and computer vision which attract many researchers attention. there are a couple of information sets pixels in an image: statistical and structural information which refer to the feature value of pixel data and local correlation of pixel data, respectively. markov random field (mrf) is a tool for modeling statistical and structural inf...

Introduction: Lung cancer is one of the most common causes of cancer-related deaths worldwide. Nowadays PET/CT plays an essential role in radiotherapy planning specially for lung tumors as it provides anatomical and functional information simultaneously that is effective in accurate tumor delineation. The optimal segmentation method has not been introduced yet, however several ...

In this work we explore a new approach to solving the problem of surface reconstruction from cross-section curves. Existing reconstruction methods focus on producing smooth interpolations and may require a large number of crosssections to recreate feature-rich objects. In the context of medical image segmentation, we make the observation that anatomical structures usually share a common overall...

Abstractive summarization is the popular research topic nowadays. Due to the difference in language property, Chinese summarization also gains lots of attention. Most of studies use character-based representation instead of word-based to keep out the error introduced by word segmentation and OOV problem. However, we believe that word-based representation can capture the semantics of the article...

A situated approach to Markovian image segmentation is proposed based on a distributed, decentralized and cooperative strategy for model estimation. According to this approach, the EM-based model estimation is performed locally to cope with spatially varying intensity distributions, as well as non-homogeneities in the appearance of objects. This distributed segmentation is performed under a col...

Similarity-based image retrieval is part of the case-based reasoning scenario. It allows for the retrieval of images from a database that are similar in some way to a given query image. It has been used in case-based reasoning systems for both image segmentation and image interpretation. Whereas case-based reasoning focuses on incremental learning of prototypical case-classes and index structur...

In current developments of CBIR system, it is desirable to design a computer program that can index the content of an image automatically into a set of perceptually significant components. Results from existing image segmentation techniques are not sufficient to represent the content of an image. Further grouping is required to produce more meaningful segmentation. This paper describes our appr...