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To extract reasonable support relations from “RGB+depth” (RGBD) images, it is very important to achieve good scene understanding. This paper proposes a novel approach to extracting accurate support relationships by analyzing the RGBD images of indoor scenes. Noting that the support relations and structure classes of indoor images are inherently related to physical stability, we construct an improved...
In this paper, a novel level set segmentation model integrating the intensity and texture terms is proposed to segment complicated two-phase nature images. Firstly, an intensity term based on the global division algorithm is proposed, which can better capture intensity information of image than the Chan–Vese model (CV). Particularly, the CV model is a special case of the proposed intensity term under...
The Recovery of a motion-blurred image is an important ill-posed inverse problem. The goal of the present work is to provide a probabilistic method for the detection of motion parameters based on the geometrical characteristic of the Fourier spectrum. To achieve this goal, the method first detects the maximum meaningful parallel alignments in the frequency domain of the blurred image using the Helmholtz...
Classification of hyperspectral image data has drawn much attention in recent years. Consequently, it contains not only spectral information of objects, but also spatial arrangement of objects. The most established Hyperspectral classifiers are based on the observed spectral signal, and ignore the spatial relations among observations. Information captured in neighboring locations may provide useful...
Texture synthesis is used to render high quality textures on surfaces, and has been widely recognized as an important research topic in surface rendering. To overcome the low efficiency of previous methods, we present a fast algorithm to synthesize texture on surfaces. First, the surfaces are segmented into a series of mapping areas and synthesis areas using constraints of normal vector error. Then...
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