A missing intensity restoration method via adaptive selection of perceptually optimized subspaces is presented in this paper. In order to realize adaptive and perceptually optimized restoration, the proposed method ge...
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The catadioptric omnidirectional sensor,called Omni-Vision,involving capture and automatic interpretation of images,depicts full horizontal panorama 360 degrees view of the *** field of view band can be easily transfo...
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The catadioptric omnidirectional sensor,called Omni-Vision,involving capture and automatic interpretation of images,depicts full horizontal panorama 360 degrees view of the *** field of view band can be easily transformed to a panoramic image and a converntional perspective ***,it has an intrinsical disadvantage that the angular resolution Omni-Vision is lower than that of conventional video *** this paper,a super-resolution method for the Omni-Vision is proposed to reconstruct high resolution panoramic transformed images,in which consecutive images obtained by rotating motion of Omni-Vision are fused using the pocs(project on convex sets) *** results are also provided to demonstrate the efficiency of the proposed method.
Lung 4D-CT plays an important role in lung cancer radiotherapy for tumor localization and treatment planning. In lung 4D-CT data, the resolution in the slice direction is often much lower than the in-plane resolution....
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ISBN:
(纸本)9781424479276
Lung 4D-CT plays an important role in lung cancer radiotherapy for tumor localization and treatment planning. In lung 4D-CT data, the resolution in the slice direction is often much lower than the in-plane resolution. For multi-plane display, isotropic resolution is necessary, but the commonly used interpolation operation will blur the images. In this paper, we present a registration based method for super resolution enhancement of the 4D-CT multi-plane images. Our working premise is that the low-resolution images of different phases at the corresponding position can be regarded as input "frames" to reconstruct high resolution images. First, we employ the Demons registration algorithm to estimate the motion field between different "frames". Then, the projections onto convex sets (pocs) approach is employed to reconstruction high-resolution lung images. We show that our method can get clearer lung images and enhance image structure, compared with the cubic spline interpolation and back projection method.
A missing intensity restoration method via adaptive selection of perceptually optimized subspaces is presented in this paper. In order to realize adaptive and perceptually optimized restoration, the proposed method ge...
详细信息
ISBN:
(纸本)9781467369985
A missing intensity restoration method via adaptive selection of perceptually optimized subspaces is presented in this paper. In order to realize adaptive and perceptually optimized restoration, the proposed method generates several subspaces of known textures optimized in terms of the structural similarity (SSIM) index. Furthermore, the SSIM-based missing intensity restoration is performed by a projection onto convex sets (pocs) algorithm whose constraints are the obtained subspace and known intensities within the target image. In this approach, a non-convex maximization problem for calculating the projection onto the subspace is reformulated as a quasi-convex problem, and the restoration of the missing intensities becomes feasible. Furthermore, the selection of the optimal subspace is realized by monitoring the SSIM index converged in the pocs algorithm, and the adaptive restoration becomes feasible. Experimental results show that our method outperforms existing methods.
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