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This paper presents an approach to improve the performance of Directional Weighted Median (DWM) Filter based restoration of images corrupted with fixed valued impulse noise. The proposed approach involves minimum absolute difference criteria to distinguish among the edge and non-edge pixels. The identified corrupted pixels are then replaced by weighted median or mean value computed within the local...
Multi-oriented dehazing in video frames is not as easy as degraded of captions or graphics or air light, which usually appears in any location or any images and has high contrast, compared to its background. Images frames are frequently despoiled by full of atmosphere haze, a phenomenon due to the particles in the air that disperse light. Haze induces a loss of contrast, its visual effect is blurring...
In today's world peoples are clicking lots of pictures and also trying to preserve there past pictures, but as the time passes that pictures got damaged. To restore that damages like scratches, overlaid text or graphics can be remove by using technique called Image Inpainting. Images Inpainting is a set of techniques for making undetectable modifications to images. Applications of image inpainting...
Impulse noise detection is the key issue, while removing random-valued impulse noise from digital images. In this paper, we present a new impulse detection algorithm based on combination of Luo-statistic and k-means clustering. This paper also presents a novel approach to measure impulse noise density level in the corrupted image, knowledge of which allows us to select suitable parameters for the...
Restoration techniques of degraded image is still a challenging task, in spite of the sophistication of the recently proposed methods. All show an outstanding performance when the image model corresponds to the algorithm assumptions but fail to retain the edges and fine structure. In this paper, a novel approach for image restoration has been developed. To show the analysis of performance of this...
Analysis of handwritten document images is one of the key areas of research in image processing domain. The objective of the analysis is to recognize the text components in an image and extract the intended information. However, inscription of handwriting usually would be on documents with rule lines, since they act as guide lines to the writer to ensure the writing remains straight and is of uniform...
We propose a self-constructing type-2 fuzzy neural network for impulse noise removal in digital images. The architecture and corresponding parameters of the network are initialized by a SVD-based self-constructing rule generation algorithm, and the initialized parameters are optimized by a hybrid learning algorithm. The trained network can be employed to detect the noisy pixels in the images corrupted...
Non-convex non-smooth (NCNS) regularization has advantages over convex regularization for restoring images, but it may lead to challenging computation. In this paper, an adaptive non-convex non-smooth (ANCNS) regularization is proposed for image restoration by using the spatial information indicator. Moreover, an efficient numerical algorithm for solving the resulting minimization problem is provided...
Deconvolution has become one of the most used methods for improving spectral resolution, and blind deconvolution as a typical method has been researched widely. However, the predefined point spread function (PSF) used in blind deconvolution method is not known exactly in practice. In general, the PSF is estimated simultaneously from the observed spectrum, but it becomes difficult when the spectroscopic...
Image de-noising is an essential intermediate step in several medical applications related to brain MRI. The noise present in brain MRI degrades the performance of computer-aided analysis of these images. Therefore, the noise should be removed prior to subsequent processing. Non-local means (NLM) is a classical de-noising algorithm, which has been successfully applied for de-noising of brain MRI....
The restoration of motion blurred images is a hot shot in the field of image processing. In this paper, The degradation model of motion blurred images is clarified, and the estimation of the PSF parameter as well as its algorithm is presented. Frequency spectrum and Radon transition are used for the length and angle calculation, then Wiener filtering and Inverse filtering are used for recovering the...
This paper proposes restoration of an image using filters before an image quality assessment is performed. Image noising is being done to a quality image by addition of impulse noise in different variances. There are two methods of image restoration namely; adaptive median filter and improved median filter. These filters are used to perform impulse noise removal function. Then the quality assessment...
Depth maps provided by Microsoft Kinect often contain large dark holes around depth boundaries and occasional missing pixels in non-occluded regions, as well as noise, which prevent their further usage in real-world applications. In this paper, we present a graph Laplacian based framework to restore missing pixels based on the strong correlation between color image and depth map. To preserve sharp...
In this paper, a new multi-scale deblurring method is proposed to remove the motion blur. The method estimates the blur kernel by an alternative algorithm at scales from coarse to fine. After the blur kernel is estimated in the finest scale, the blurred image is restored via image deconvolution. To remove the ringing artifacts, we propose a smooth regions constraint. Combining with the noise prior,...
In single photon emission computed tomography (SPECT), the Poisson noise in sinogram data is one of the major degrading factors that jeopardize the quality of reconstructed images. The common strategy to reduce noise in SPECT images is to apply low-pass pre- or post-processing filters, which suppress the noise by attenuating the high frequency components that can contain valuable edge/detail information...
To further alleviate the ionizing radiation damage of computed tomography (CT), we propose a method of sparse-view reconstruction based on low-dose CT projection data. It first utilizes a penalized weighted least square (PWLS) restoration for low-dose CT projection based on noise modeling. Then the CT images are reconstructed from fewer views of denoised projection data. Reconstruction results from...
A block-based adaptive median filter, which aims to purify impulse noise from an MRI image, is discussed in the paper. The proposed filter blocks the image into several sub-images, and calculates the standard deviation of each sub-image. During filtering process, each point of the sub-image needs to be judged whether it is noise point or not, according to the average value of the filtering window...
In view of the selection of structuring elements problem in morphological filters, this paper presents a new method to generate structuring elements for spatially-variant (SV) morphology. This method takes the theory of amoeba morphology as a foundation and does distance transform from soft boundary to inner hard center in predefined neighborhood through a metric according to the gradient criteria...
Image restoration issues are closely connected with imaging systems, where image resolution is limited by diffraction phenomenon. The presented work is motivated by the super acuity of the Human vision, where the restoration step is implemented by some kind of parallel processor unit — neural network. The de-convolution process is formulated as a machine learning problem and the inverse operator is...
Deblurring and destriping are both classical problems for remote sensing images, which are known to be difficult. Treating deblurring and destriping separately, such a straightforward approach, however, suffers greatly from the defective output. This paper shows that the two problems can be successfully solved together and benefit greatly from each other within a unified variational framework. To...
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