This report proposes a new image segmentation method with a multi-resolution mechanism. In this method, the high accuracy on image edge extraction and image texture evaluation is realized. The proposed method employs the edge extraction based on the average values of intensities in a small image part and also the texture evaluation based on the co-occurrence probability of a local image area. I...

In practice, image segmentation can be performed in many areas like medical and satellite communications to detect objects and regions in the image.The texture enhancement methods representing all texture information using a single image component. In previous texture enhancement methods reduce noise or artifacts in the image to highlight the textures with the help of filters which reduces the ...

An image compression approach capable of exploiting redundancies in groups of images is introduced. The approach is based on image segmentation, texture analysis and texture synthesis. The proposed algorithm extracts textured regions from an image and merges them with similar texture data from other images, in order to take advantage of textural re-occurrences between the images. The texture ex...

We develop an approach to image segmentation for natural scenes containing image texture. One general methodology which shows promise for solving this problem is to characterize textured regions via their responses to a set of filters. However, this approach brings with it many open questions, including how to combine texture and intensity information into a common descriptor and how to deal wi...

We develop an approach to image segmentation for natural scenes containing image texture. One general methodology which shows promise for solving this problem is to characterize textured regions via their responses to a set of lters. However, this approach brings with it many open questions, including how to combine texture and intensity information into a common descriptor and how to deal with...

Over the last decade, several studies on texture analysis propose to model texture as a probabilistic process that generates small texture patches. In these studies, texture is represented by means of a frequency histogram that measures how often texture patches from a codebook occur in the texture. In the codebook, the texture patches are represented by, e.g., a collection of filter bank respo...

In this paper a combined statistical and structural approach has been employed for texture representation. A set of Texture Primitives has been suggested. These primitives are basically tested for the presence of texture by conducting a suitable statistical test called Nair’s test. The set of universal primitives are labeled as local descriptor and the frequency of occurrences of these primitiv...

Retexturing is the process of realistically replacing the texture of an object or surface in a given image by a new, synthetic one, such that texture distortion as well as lighting conditions of the original image are preserved. The key challenge is to separate the shading information from the actual local texture and to retrieve the texture distortion from an image without any knowledge of the...

Analysis of texture within tumours on computed tomography (CT) is emerging as a potentially useful tool in assessing prognosis and treatment response for patients with cancer. This article illustrates the image and histological features that correlate with CT texture parameters obtained from tumours using the filtration-histogram approach, which comprises image filtration to highlight image fea...