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Existing dual image deblurring methods usually model blurred image pairs being taken from exactly the same viewpoint and restore a single clear image. This imposes a strong assumption that the latent clear images of both images must be completely identical. In contrast to this restricted scenario, we assume that the restored pair are different, but can be approximated by image warping due to small...
Depth maps generated by Kinect cameras often contain a significant amount of missing pixels and strong noise, limiting their usability in many computer vision applications. We present a new energy minimization method to fill the missing regions and remove noise in a depth map, by exploiting the strong correlation between color and depth values in local image neighborhoods. To preserve sharp edges...
Blurred image restoration is a longstanding and critical research problem. We addressed this problem using Expectation Maximization (EM) based approach in wavelet domain. The sparsity property of wavelet coefficients is modeled using the class of Gaussian Scale Mixture (GSM), which represents the heavy-tailed statistical distribution, suitable for natural images. The underlying original image and...
This paper presents a new binarization method for color images of degraded historical document. The proposed method makes use of local image equalization based on color constancy, and an extension to the standard difference of Gaussians edge detection operator, XDoG. The binarization is achieved after three main steps: the first step removes undesirable degradation artifacts using a local image equalization...
Historical documents suffer from different types of degradation and noise such as background variation, uneven illumination or dark spots. In case of double-sided documents, another common problem is that the back side of the document usually interferes with the front side because of the transparency of the document or ink bleeding. This effect is called the show through phenomenon. Many methods are...
Sparse representation based image restoration techniques have shown to be successful in solving various inverse problems such as denoising, in painting, and super-resolution, etc. on natural images and videos. In this paper, we explore the use of sparse representation based methods specifically to restore the degraded document images. While natural images form a very small subset of all possible images...
In this work, the structures of the Inverse Difference Pyramid (IDP) and its modification — the Reduced IDP (RIDP), are compared and evaluated with the famous Laplacian Pyramid for multi-level decomposition of digital images. The computational complexity of both decompositions is also evaluated. On the basis of the comparison of the block diagrams, which represent the recursive calculation of the...
Denoising is an important part of digital image processing. Adaptive Fidelity term Total Variation (AFTV) method can effectively remove the noise and can preserve the edge and detail information of the image. However, noise variance should be given in the method, and the mothed is sensitive to noise, which will lead to unsatisfactory denoising results in edges of image. Therefore, an improved Adaptive...
Image Restoration is a field of Image Processing in which recovering an original and sharp image from a degraded image. Purpose of this paper is to restore the blurred images using blind deconvolution algorithm with canny edge detector. Initially original image is blurred using Gaussian filter. Then in the edges of the blurred image, the ringing effect can be detected using Canny Edge Detection method...
To enhance high frequency details of image super-resolution restoration, an algorithm based on improved MAP estimation is proposed. In this paper, POCS and MAP are combined in a special way. POCS is used in the MAP estimation so that advantages of the both algorithms can be taken. Experiment shows it is effective by comparing with the results of typical MAP method.
The Perona Malik filter forms the base for various classical diffusion filters. It takes its origin from the heat equation. The images undergo an iterative diffusion process and the noise is removed gradually after each iteration. The basic concept behind various prominent image processing methods like image smoothing, enhancement, denoising etc is mostly based upon PM equation. But the main drawback...
Fog reduces contrast and thus the visibility of vehicles and obstacles for drivers. Each year, this causes traffic accidents. Fog is caused by a high concentration of very fine water droplets in the air. When light hits these droplets, it is scattered and this results in a dense white background, called the atmospheric veil. As pointed in [1], Advanced Driver Assistance Systems (ADAS) based on the...
Image restoration is a research field that attempts to recover a blurred and noisy image. Since it can be modeled as a linear system, we propose in this paper to use the meta-heuristics optimization algorithm Harmony Search (HS) to find out near-optimal solutions in a Projections Onto Convex Sets-based formulation to solve this problem. The experiments using HS and four of its variants have shown...
Ultrasound imaging plays a crucial roles in medical field to estimate kidney size, position, appearance and helps to detect structural abnormalities as well as the presence of cysts, stones, cancer, congenital anomalies, swelling, blockage of urine flow etc. But presence of speckle noise and low contrast in ultrasound images, detection of kidney is a difficult as well as challenging task. In this...
Based on the research and analysis of the evolution process of three different level models, a concept of anisotropic diffusion equation which gathers all the majority of them is introduced. Furthermore, we propose the definition of UPDE (Universal Partial Differential Equations)-a more general equation, which is better in diffusion filtering and also keeps the edge's information in an image at the...
In the process of image restoration, the denoising is an important step. Several models of non-linear diffusive filters requiring solving partial differential equations have been proposed in the literature [1], [2], [3], [4], [5], [6], [7] during the last decades. The existence and uniqueness of a solution in Hilbert space has been established under suitable conditions on the filtering function for...
Properties and performances of associative memories, based on Complex-valued Synergetic Computer (CVSC), are explored in this paper. In the proposed CVSC, the state vectors, prototype vectors and order parameters are encoded by complex values. This CVSC is extended from the conventional Synergetic Computer (RVSC) in which the order parameters produce real values in processing real-valued input and...
Image restoration (deconvolution) is a basic step for image processing, analysis and computer vision. We addressed blurred image deconvolution problem using Expectation maximization (EM) based approach in the wavelet domain. The sparsity property of wavelet coefficients is modelled using the class of Gaussian Scale Mixture (GSM), which represents the heavy-tailed statistical distribution. The maximum...
This paper presents an Image Filter with noise detector using Fuzzy Logic and Particle Swarm Optimization (PSO), which is called the IFFLPSO filter, for removal and restoration of impulse noises. In IFFLPSO filter, the fuzzy logic is employed to efficiently design the noise detector. The proposed filter effectively judges the input pixel vector whether it is corrupted or not. Meanwhile, the particle...
Total variation has been used as a popular and effective image prior model in regularization-based image blind restoration, because of its ability to preserve edges. However, as the total variation model favors a piecewise constant solution, the processing results in the flat regions of the image being poor, and it cannot automatically balance the processing strength between different spatial property...
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