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This paper presents a sparse representation based image inpainting method using local patch analysis and geometric structure based feature extraction. In local patch analysis, we approximate the target region by weighted average of some local patches which are frequently occurred within a neighborhood. Local patch statistics is applied to find the most relevant neighbors for each target patch. Further...
Cosparse analysis model has shown its superior performance in image reconstruction. However, this analysis frame has not been exploited yet for hyperspectral image restoration task. An analysis operator learning method called GOAL (GeOmetric Analysis operator Learning) is applied for hyperspectral image. Considering the correlation of the hyperspectral bands, the hyperspectral images were cropped...
Underwater images suffer from severe perceptual/visual degradation, due to the dense and non-uniform medium, causing scattering and attenuation of the propagated light that is sensed. Typical restoration methods rely on the popular Dark Channel Prior to estimate the light attenuation factor, and subtract the back-scattered light influence to invert the underwater imaging model. However, as a consequence...
Visual texture modeling based on multidimensional mathematical models is the prerequisite for both robust material recognition as well as for image restoration, compression or numerous physically correct virtual reality applications. A novel multispectral visual texture modeling method based on a descriptive, unusually complex, three-dimensional, spatial Gaussian mixture model is presented. Texture...
For underwater robotics applications involving monitoring and inspection tasks, it is important to capture quality color images in real time. In this paper, we propose a statistically learning method with an automatic selection of the training set for restoring the color of underwater images. Our statistical model is a Markov Random Field with Belief Propagation (MRF-BP). The quality of the results...
This paper presents a fast deblurring algorithm to remove camera motion blur from a single photograph using built-in gyroscopes and strong edge prediction. An inaccurate blur kernel or point spread function (PSF) usually leads to an unsatisfying restored result. Hence, we propose a robust three-phase method for accurate PSF estimation. In the first stage, we utilize the embedded gyroscopes to compute...
Standard decompression of JPEG images produces artifacts along edges and a disturbing checkerboard pattern. To reduce these artifacts, decompression can be formulated as an image reconstruction problem within Bayesian maximum a posteriori probability framework. In this type of problem, the prior information about an image is typically given by the l1 norm of its sparse domain representation. In this...
With the increasing use of telemedicine there is a great demand in real-time processing and transmission of medical images. Noise is one of the important factors that degrade the quality of medical images. Impulse noise is a common noise that could be caused by malfunctioning of sensors or by data transmission errors. It is one the most common noises that have extensively been studied in recent years...
Essential image processing and analysis tasks, such as image segmentation, simplification and denoising, can be conducted in a unified way by minimizing the Mumford-Shah (MS) functional. Although seductive, this minimization is in practice difficult because it requires to jointly define a sharp set of contours and a smooth version of the initial image. For this reason, various relaxations of the original...
Recently, a series of advances were made for image restoration tasks such as image denoising and single image super-resolution. It is particularly remarkable that methods employing different formulations and assumptions achieve comparable top performances. Moreover, the top methods operate at their best on some particular image contents and poorer on other. No method is the best on all the image contents...
This contribution deals with image restoration in optical systems with coherent illumination, which is an important topic in astronomy, coherent microscopy and radar imaging. Such optical systems suffer from wavefront distortions, which are caused by imperfect imaging components and conditions. Known image restoration algorithms work well for incoherent imaging, they fail in case of coherent images...
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