Considerably research has been conducted on automated and semi-automated techniques that incorporate image textural information into the decision process as an alternative to improve the information extraction from images while reducing time and cost. The challenge is the selection of the appropriate texture operators and the parameters to address a specific problem given the large set of avail...

This paper pertains to the recognition of textural regions for color video analysis. The proposed scheme uses the covariance of 2-order statistics on the wavelet domain, between the different color channels of the video frames. These features, named as Color Wavelet Covariance (CWC), are used as color textural descriptors. A Support Vector Machine was chosen for the classification of the CWC fe...

As texture represents one of the key perceptual attributes of any object, integrating textural information into existing video object segmentation frameworks affords the potential to achieve semantically improved performance. While object segmentation is fundamentally pixel-based classification, texture is normally defined for the entire image, which raises the question of how best to directly ...

a r t i c l e i n f o Keywords: Extended pruning Multi-scale textural analysis Neural networks QuickBird Urban land-use Very high-resolution panchromatic data WorldView-1 The successful launch of panchromatic WorldView-1 and the planned launch of WorldView-2 will make a major contribution towards the advancement of the commercial remote sensing industry by providing improved capabilities, more ...

Abstract. The choice of natural image prior decides the quality of restored image. Recently successful algorithms exploit heavy-tailed gradient distribution as image prior to restore latent image with piecewise smooth regions. However, these prior assumed also remove the mid-frequency component such as textural details regions while they preserve sharp edges. That because gradient profile in fr...

We introduce a novel computational framework to enable automated identification of texture and shape features of lesions on (18)F-FDG-PET images through a graph-based image segmentation method. The proposed framework predicts future morphological changes of lesions with high accuracy. The presented methodology has several benefits over conventional qualitative and semi-quantitative methods, due...