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Error Concealment in Image Communication Using Edge Map Watermarking and Spatial Smoothing  [PDF]
Shabnam Sodagari,Peyman Hesami,Alireza Nasiri Avanaki
Computer Science , 2010,
Abstract: We propose a novel error concealment algorithm to be used at the receiver side of a lossy image transmission system. Our algorithm involves hiding the edge map of the original image at the transmitter within itself using a robust watermarking scheme. At the receiver, wherever a lost block is detected, the extracted edge information is used as border constraint for the spatial smoothing employing the intact neighboring blocks in order to conceal errors. Simulation results show the superiority of our technique over existing methods even in case of high packet loss ratios in the communication network.
An Improved Grunwald-Letnikov Fractional Differential Mask for Image Texture Enhancement
Vishwadeep Garg,Kulbir Singh
International Journal of Advanced Computer Sciences and Applications , 2012,
Abstract: Texture plays an important role in identification of objects or regions of interest in an image. In order to enhance this textural information and overcome the limitations of the classical derivative operators a two-dimensional fractional differential operator is discussed, which is an improved version of the Grunwald-Letnikov (G-L) based fractional differential operator. A two dimensional-isotropic gradient operator mask based on G-L fractional differential is constructed. This nonlinear filter mask is implemented on various texture enriched digital images and enhancement of features of image is controlled by varying the intensity factor. In order to analyze the enhancement quantitatively, information entropy and average gradient are the parameters used. The results show that with improved version of Grunwald-Letnikov, fractional differential operator information entropy of image is improved by 0.5
Lagrange Gradient Mask for Optical Image Processing
Falih Ahmad, Matthew Gilbert, Stephen Myers, José Pacheco, Ray Castellane and Ernest Miller
The Open Optics Journal , 2007, DOI: 10.2174/1874328500701010004]
Abstract: Masks are used in optical image processing. They are used to generate gradient maps. These maps are applicable to the enhancement of feature extraction and edge detection. Lagrange mask is presented in this letter and criteria for the characterizations of mask performance are given. Through an illustration the performance of the presented mask is demonstrated where it is compared to that of Gabor mask. Results from the illustration support the applicability and suitability of Lagrange mask for the generation of gradient maps from a noise corrupted optical image.
An Enhanced Procedure for Image Segmentation and Smoothing  [PDF]
V.S. Giridhar Akula,P. Chandrasekhar Reddy,V. Rajaraman,A.V. Sasidhar
Journal of Applied Sciences , 2007,
Abstract: This study aims at the development of an enhanced procedure for image segmentation and smoothing. The segmentation procedure uses region growing and merging process around seeds. This study identified different segmentation methods and their limitations. The recent developments in image segmentation and smoothing are very sensitive to broken edges. This research proposes an enhanced procedure to overcome this limitation. Our enhanced paradigm is developed on some broken images (like the Diatom images in this analysis). The concepts of PDE (Partial Differential Equations), markers, anisotropic filters and neighborhood interpolation are used for this purpose. We have prepared an enhanced procedure called SoS for image segmentation and smoothing.
Multiple -window Processing of SAR Image with Speckle-smoothing and Edge-preserving

Pang Xiaohong,

遥感学报 , 1998,
Abstract: In the processing of Synthetic Aperture Radar (SAR) Images, a large window size, which is often used in estimating the local statistics of the image and filtering the speclke is needed. On the other hand, contrary, detection of edges and textural features often need small sized windows. Normal filters, which are intermediary ofthe two above, don't give better results. This paper presents a new effective algorithm to solve the problem. In this method, the edges and the textural features of the SAR images are presented so the the problem of edge smearing in the normal filtering algorithm is avoid and the speckles are filtered effectively.
A Variation Method Based on Convolution Integral for Image Denoising

ZHANG Jun,WEI Zhi-hui,

中国图象图形学报 , 2008,
Abstract: It is important to preserve more detailed information in image denoising.In this paper,we extend the total variation model for image denoising is which based on gradient to a new model based on fractional derivative,and then making use of the characteristic that fractional derivative and convolution integral have the same discrete formula in certain situation,We propose a variational model based on convolution integral which can be computed easily.The numerical results show that our model can not only better improve the PSNR of image,but also preserve more detailed information.
Improved Edge Awareness in Discontinuity Preserving Smoothing  [PDF]
Stuart B. Heinrich,Wesley E. Snyder
Computer Science , 2011,
Abstract: Discontinuity preserving smoothing is a fundamentally important procedure that is useful in a wide variety of image processing contexts. It is directly useful for noise reduction, and frequently used as an intermediate step in higher level algorithms. For example, it can be particularly useful in edge detection and segmentation. Three well known algorithms for discontinuity preserving smoothing are nonlinear anisotropic diffusion, bilateral filtering, and mean shift filtering. Although slight differences make them each better suited to different tasks, all are designed to preserve discontinuities while smoothing. However, none of them satisfy this goal perfectly: they each have exception cases in which smoothing may occur across hard edges. The principal contribution of this paper is the identification of a property we call edge awareness that should be satisfied by any discontinuity preserving smoothing algorithm. This constraint can be incorporated into existing algorithms to improve quality, and usually has negligible changes in runtime performance and/or complexity. We present modifications necessary to augment diffusion and mean shift, as well as a new formulation of the bilateral filter that unifies the spatial and range spaces to achieve edge awareness.
Texture Analysis Based Detail Preserving Smoothing Filter

ZHU Ju hu,YANG Xin,LI Jun,SHI Peng fei,

中国图象图形学报 , 2001,
Abstract: Smoothing is an important topic in image processing area. However, smoothing and edge preserving are hard to achieve simultaneously. In this paper, we propose an improved adaptive detail preserving smoothing algorithm using multiscale and multidirectional mask to deal with this issue. Before smoothing, complexity of texture is calculated according to the edge map. We ourselves define a measurement of complexity of texture which is simple and fast for operation. For the area with large value of texture complexity, that is the area with details, "stick" is used for smoothing to preserve these minute features, while for the area with small value, block mask is employed to speed and emphasize smoothing. As to using "stick", eight different directions are considered to make the most suitable mask take effect. To achieve that, we take the standard deviation as the criterion, small standard deviation denoting homogeneous area and suiting for being taken as the smoothing mask. This method, to some extent, is effective for both smoothing and edge preserving, mainly because it selects different mask according to the local feature of the image utilizing texture analysis. Compared with other methods, including traditional Median Filter, MWMF, Nagao's Filter, DMF and PDE, this algorithm is easy and faster to implement in computer and has better performance.
Object Edge Smoothing by Wavelet Transformation  [PDF]
Zheng Xiaodong,Huang Xinghan,Wang Ming
Information Technology Journal , 2005,
Abstract: In order to solve problem that most 2D (Two-dimensional) shape representations don’t fit for wavelet transformation processing, a new method of 2D shape representation has been put forward. It stores object borderline pixels coordinate value (xi, yi) into two arrays x = X[i]; y = Y[i] by the sequence of object borderline tracking result, object boundary has been represented by this two array. It changes a 2D image problem into two single dimension arrays’ problem and can be processed by wavelet transformation. Then make full use of the ability of time and frequency localization of wavelet transformation and find characters both in time and frequency. The boundaries leaps can be distinguish from noise. This technique has been applied in workpiece boundary noise reducing. And it shows that noise can be eliminated and boundaries corners are remained at same time.
An Enhancement of Classical Unsharp Mask filter for Contrast and Edge Preservation  [PDF]
Gurpreet Kaur
International Journal of Engineering Sciences & Research Technology , 2013,
Abstract: Various images are low quality, difficult to detect and extract information. Therefore, enhancement of contrast and Sharpness of an image is required in many applications. Unsharp masking is a good tool for sharpness enhancement: it is an anti-blurring filter. By using Unsharp masking algorithm for sharpness enhancement, the resultant image suffering with two problems, first one is halo appears around the image and second one is rescaling process is needed for the resultant image. The aim of this paper is to enhance the contrast and sharpness of an image simultaneously and to solve the problems. Medical images are one of the fundamental images, because they are used in more sensitive field. In order to improve the visual quality of medical images, the proposed algorithm working on the medical images for their improved diagnostic with enhanced classical Unsharp mask filter which will not only preserve the edge but also the contrast is maintain i.e. suitable for body part. Experimental results, which comparable to recent published results, shows that proposed algorithm is significantly improve the sharpness and contrast of an image. This makes the proposed algorithm practically useful.
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