We have developed a novel interpolation method for images containing text, graphics and natural scenes. The method allows us to select the best interpolation algorithm for different regions of an image. In particular,...
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ISBN:
(纸本)9780819489425
We have developed a novel interpolation method for images containing text, graphics and natural scenes. The method allows us to select the best interpolation algorithm for different regions of an image. In particular, we segment the image into graphical and natural regions and use the appropriate algorithm for each region. The natural regions are interpolated using a current state-of-the-art algorithm. However, when applied to graphical images, the current state-of-the-art interpolators tend to produce artifacts at edge discontinuities. Thus, we developed a novel approach which we call Low Entropy Interpolation (LEI) algorithm for the graphical images. The LEI algorithm is highly non-linear and produces very sharp edges with very few defects necessary for good quality interpolation of graphical images.
This paper introduces a new spatial edge oriented algorithm for automatic digital inpainting. The approach is based on the Laguerre Gauss analysis of the structure information of the regions surrounding the damaged po...
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ISBN:
(纸本)9780819489425
This paper introduces a new spatial edge oriented algorithm for automatic digital inpainting. The approach is based on the Laguerre Gauss analysis of the structure information of the regions surrounding the damaged portions of the image, extrapolating in automatic way the gradient of the luminance and color in missing areas this estimation is made of a least square fitting algorithm from simplified edge lines that stood on the boundary of missing region. The reconstruction of the unknown parts is automatically obtained by a variational method that uses the predicted gradient information imposing smoothing constraints on luminance and color level. Experiments on a number of images show the effectiveness of the proposed algorithm in smooth areas, as well as in areas with edges and/or textured.
In this work a novel technique for detecting and segmenting textured areas in natural images is presented. The method is based on the circular harmonic function, and, in particular, on the Laguerre Gauss functions. Th...
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ISBN:
(纸本)9780819489425
In this work a novel technique for detecting and segmenting textured areas in natural images is presented. The method is based on the circular harmonic function, and, in particular, on the Laguerre Gauss functions. The detection of the textured areas is performed by analyzing the mean, the mode, and the skewness of the marginal densities of the Laguerre Gauss coefficients. By using these parameters a classification of the patch and of the pixel, is performed. The feature vectors representing the textures are built using the parameters of the Generalized Gaussian Densities that approximate the marginal densities of the Laguerre Gauss functions computed at three different resolutions. The feature vectors are clustered by using the K-means algorithm in which the symmetric Kullback-Leibler distance is adopted. The experimental results, obtained by using a set of natural images, show the effectiveness of the proposed technique.
In this paper, new methods are addressed for impulse and speckle noise removal in images. The approach is based on the fusion of noise detection and image inpainting techniques. To avoid destroying the real structures...
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ISBN:
(纸本)9780819489425
In this paper, new methods are addressed for impulse and speckle noise removal in images. The approach is based on the fusion of noise detection and image inpainting techniques. To avoid destroying the real structures of the image, the noise areas are first recognized to be repaired by an inpainting algorithm, subsequently. To distinguish the impulse noise areas in the image, a Neuro-Fuzzy model is employed and, to extract the speckled regions an algorithm is proposed based on Frost filtering and image resizing. The advantage of inpainting technique over the regular filtering methods is that it will be easier to generalize to all types of noise. Once we detect the damaged pixels in the image, the inpainting algorithm will be able to repair them. Various types of images under three levels of noise are tested using PSNR and SSIM measures. The experimental results demonstrate the great ability of the new approaches to suppress the noise properly, while preserving critical details of the image.
image enhancement algorithms attempt to improve the visual quality of images for human or machine perception. Most direct multi-scale image enhancement methods are based on enhancing either absolute intensity changes ...
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ISBN:
(纸本)9780819489425
image enhancement algorithms attempt to improve the visual quality of images for human or machine perception. Most direct multi-scale image enhancement methods are based on enhancing either absolute intensity changes or the Weber contrast at each scale, and have the advantage that the visual contrast is enhanced in a controlled manner. However, the human visual system is not adapted to absolute intensity changes, while the Weber contrast is unstable for small values of background luminance and potentially unsuitable for compleximage patterns. The Michelson contrast measure is a bounded measure of contrast, but its expression does not allow a straightforward direct image enhancement formulation. Recently, a second derivative-like measure of contrast has been used to assess the performance of image enhancement algorithms. This measure is a Michelson-like contrast measure for which a direct image enhancement algorithm can be formulated. Accordingly, we propose a new direct multi-scale image enhancement algorithm based on the SDME in this paper. Experimental results illustrate the potential benefits of the proposed algorithm.
CT (Computed tomography) is a widely employed imaging modality in the medical field. Normally, a volume of CT scans is prescribed by a doctor when a specific region of the body (typically neck to groin) is suspected o...
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ISBN:
(纸本)9780819489425
CT (Computed tomography) is a widely employed imaging modality in the medical field. Normally, a volume of CT scans is prescribed by a doctor when a specific region of the body (typically neck to groin) is suspected of being abnormal. The doctors are required to make professional diagnoses based upon the obtained datasets. In this paper, we propose an automatic registration algorithm that helps healthcare personnel to automatically align corresponding scans from 'Study' to 'Atlas'. The proposed algorithm is capable of aligning both 'Atlas' and 'Study' into the same resolution through 3D interpolation. After retrieving the scanned slice volume in the 'Study' and the corresponding volume in the original 'Atlas' dataset, a 3D cross correlation method is used to identify and register various body parts.
The Intensity Constrained Flat Kernel Filtering (ICFK) scheme is a dual domain (spatial and intensity) nonlinear framework which has been shown to generate useful filters for imageprocessing. This paper proposes a ne...
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ISBN:
(纸本)9780819489425
The Intensity Constrained Flat Kernel Filtering (ICFK) scheme is a dual domain (spatial and intensity) nonlinear framework which has been shown to generate useful filters for imageprocessing. This paper proposes a new filter developed within the ICFK framework. Although local in nature the filter is designed to suppress large scale spatial features within the image. As in every other filter derived within the scheme the suppressed features are defined by two parameters: size of the kernel and intensity range. The filter, a single-step procedure, is applied to removal of hair artifacts in skin lesion epiluminescence microscopy images, the task essential in assisting in automated segmentation of imaged area into lesion and surrounding skin. Results of the experiments on 400 dermatoscopic images of lesions with hair indicate suitability of the method as an aid in lesion segmentation by suppressing hair or vascular features near the lesion borders.
In this paper, we study a plane-dependent technique that reduces dot-on-dot printing in color images, and apply this technique to a GPU-based error diffusion halftoning algorithm. We design image quality metrics to pr...
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ISBN:
(纸本)9780819489425
In this paper, we study a plane-dependent technique that reduces dot-on-dot printing in color images, and apply this technique to a GPU-based error diffusion halftoning algorithm. We design image quality metrics to preserve mean color and minimize colorant overlaps. We further use randomized intra-plane error filter weights to break periodic structures. Our GPU implementation achieves a processing speed of 200 MegaPixels/second for RGB color images, and a speedup of 30 - 37x over a multi-threaded implementation on a dual-core CPU. Since the GPU implementation is memory bound, we essentially get the image quality benefits for free by adding arithmetic complexities for inter-plane dependency and error filter weights randomization.
During the last decades, statistical models, such as the Ising model, have become very useful in describing solid state systems. These models excel in their simplicity and versatility. Furthermore, their results get q...
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ISBN:
(纸本)9780819489425
During the last decades, statistical models, such as the Ising model, have become very useful in describing solid state systems. These models excel in their simplicity and versatility. Furthermore, their results get quite often accurate experimental proofs. Leading researchers have used them successfully during the last years to restore images. A simple method, based on the Ising model, was used recently in order to restore B/W and grayscale images and achieved preliminary results. In this paper we outline first the analogy between statistical physics and imageprocessing. Later, we present the results we have achieved using a similar, though more complex iterative model in order to get a better restoration. Moreover, we describe models which enable us to restore colored images. Additionally, we present the results of a novel method in which similar algorithms enable us to restore degraded video signals. We confront our outcomes with the results achieved by the simple algorithm and by the median filter for various kinds of noise. Our model reaches PSNR values which are 2-3 dB higher, and SSIM values which are 15%-20% higher than the results achieved by the median filter for video restoration.
Most of cameras follow pinhole camera model. However, result of this model makes some undesirable effects in wide angle lens. The most serious problem among these effects is radial distortion which appears heavily in ...
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ISBN:
(纸本)9780819489425
Most of cameras follow pinhole camera model. However, result of this model makes some undesirable effects in wide angle lens. The most serious problem among these effects is radial distortion which appears heavily in fish-eye images. Several geometric models for correcting radial distortion of fish-eye lens are developed. Most of these models require only one parameter. However, correcting with one parameter is limited to correct both central and outer part simultaneously. Aim of this paper is to solve this problem. The proposed method is able to correct radial distortion of both areas using region adaptive distortion parameter. Each parameter is determined by considering amount of distortion in each region respectively. Also, the proposed method modifies the existing division model to correct radial distortion of both regions. Experimental results show that radial distortions in both areas are corrected.
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