ملخص البحث :

The goal of edge-aware filtering is to smooth outsmall-scale structures while preserving large object bound-aries. A fundamental idea to design such filters is to avoidsmoothing across strong edges. In this paper, we explore anew approach which iteratively adds the edge informationback to a smoothed image. We study the smoothed image asthe starting point of the iteration and the optimal stoppingcriterion. We demonstrate that in a wide range of applica-tionstheproposedtechniquecanproducecompetitiveresultsas those of state-of-the-art edge-aware filters. In particular,the proposed algorithm has the best performance in texturesmoothing.

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The aim of structure extraction is to decompose an image into prominent struc- tures and textures. In this paper, we present a new structure extraction method which has two main steps. First, high-frequency components due to the texture information in the orig- inal image are alleviated by a pre-smoothing filter. The result is then processed by a new anisotropic diffusion algorithm which uses a second neighbour derivative (SND) operator instead of the first neighbour derivative operator. We have demonstrated that the SND oper- ator is better suited for applications such as texture smoothing. We have also presented a detailed study of the proposed method including the selection of the pre-smoothing filter, the number of iterations, and the scale parameter in the anisotropic diffusion algorithm. We have conducted experiments to compare the performance of the proposed method with those state-of-the-art structure extraction algorithms in a wide range of image editing appli- cations such as: superpixel segmentation, texture transfer, contrast enhancement, and pencil drawing. We show that while the running speed of the proposed method is the fastest, its performance is competitive to other methods.

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Structure-texture decomposition smoothing has been extensively studied due to its wide range of appli- cations in computational photography and image processing. In this paper, we propose a new structure- texture decomposition algorithm which is based on two fundamental ideas: (1) guidance image and (2) iterative smoothing. The guidance image is generated by mitigating high-frequency oscillatory compo- nents in the original image. The result is then incorporated in a new generic iterative framework which makes use of well-known guided edge-reserving filters such as bilateral filter (BF), guided filter (GF), domain transform filter (DTF), and the extended Bayesian model averaging filter (BMA) called guided Bayesian model averaging filter (GBMA) to achieve texture smoothing. We have presented a detailed study of the proposed algorithm including: guidance image generation, an evaluation of the guided edge- preserving filters which are incorporated in the proposed iterative framework, the number of iterations for the proposed iterative structure, and the selection of guided edge-preserving filter. We demonstrate that the proposed method is a flexible and effective tool for a wide range of image editing applications including: image abstraction, color pencil drawing, content-aware image resizing, and texture editing. In particular, the proposed approach has the best performance in structure-texture decomposition for an image with low-contrast features.

ملخص البحث :

The bilateral filter (BF) is a non-linear filter that spatially smooths images with awareness of large structures such as edges. The level of smoothness applied to a pixel is constrained by a photometric weight, which can be obtained from the same image to be filtered (in case of the original BF) or from a guided image (in case of the joint/cross BF). In this study, the authors propose a new filter called the semi-guided BF which is derived from solving a non-linear constraint least square problem. The proposed filter's photometric weight incorporates information from the image to be filtered and the guided image. They propose a fast implementation of the filter based on layer approximation. They also study the iterative application of the proposed filter and show that the filter can preserve large structures while smoothing out small structures. This makes the proposed filter an efficient and effective tool for structure-aware image smoothing. Experimental results have demonstrated that performance of the proposed filter is comparable to those of the state-of-the-art algorithms.

ملخص البحث :

Stereo matching is the process of finding disparity map between a pair of stereo images. Markov Random Field (MRF) model has been used in stereo matching algorithms in which the goal is to minimize total data, smoothness and occlusion cost. Recent MRF based stereo matching algorithms assign the same smoothness cost to adjacent pixels which is not effective at objects boundaries. In this paper, we propose a method to constrain the smoothness cost such that the cost applied to disparity discontinuity within an object is higher than that of the object’s boundary. Data cost function is also normalized before computing its probability distribution function (PDF) to enforce an uniform PDF for the entire image. Experimental results have demonstrated that the proposed method is competitive to the state-of-the-art stereo matching algorithms.

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An efficient low complexity puncturing method has studied to achieve rate compatible. The parallel concatenation codes are use mixing of one component of Quasi-Cyclic (QC) low- density parity check codes LDPC codes with two components of (LDPC) in linear coding. The proposed QC-PCGC have lower computation complexity when compared with traditional punctured PCGC. The decreasing in the complexity analysis yields to the reducing in the memory requirement for the encoding/decoding system. It is possible to use the suggested coding system structure in the future communication applications like fifth generation (5G), where it is needed to have coding flexibility, with less complexity in encoding and decoding.

ملخص البحث :

Edge-aware smoothing has proved to be a fundamental technique for various image processing and computer vision tasks. In this paper, we introduce a local, non-iterative and effective edge-preserving filter namely guided adaptive interpolation filter (GAIF). GAIF can be used as a post-processing step after any smoothing filter to improve its edge preservation performance without reformulation. GAIF has an O(N) computation complexity where N is the total number of pixels in the image. To further increase the efficiency of GAIF at edge-preservation, two techniques are introduced and demonstrated. GAIF efficiency is demonstrated and compared to state-of-the-art techniques on a number of tasks including image smoothing, flash/no-flash image denoising/fusion, single image dehazing and image details enhancement.

ملخص البحث :

Smoothing and sharpening are two fundamental image processing operations. The latter is usually related to the former through the unsharp masking algorithm. In this paper, we develop a new type of filter which performs smoothing or sharpening via a tuning parameter. The development of the new filter is basedon(1)anewLaplacian-basedfilterformulationwhichunifiesthesmoothingandsharpeningoperations, (2) a patch interpolation model similar to that used in the guided filter which provides edge-awareness capability, and (3) the generalized Gamma distribution which is used as the prior for parameter estimation. We have conducted detailed studies on the properties of two versions of the proposed filter (self-guidance and external guidance). We have also conducted experiments to demonstrate applications of the proposed filter. In the self-guidance case, we have developed adaptive smoothing and sharpening algorithms based on texture, depth and blurriness information extracted from an image. Applications include enhancing human face images, producing shallow depth of field effects, focus-based image enhancement, and seam carving. In the external guidance case, we have developed new algorithms for combining flash and no-flash images and for enhancing multi-spectral images using a panchromatic image.

ملخص البحث :

Edge-aware smoothing is an essential tool for computer vision, graphics and photography. In this paper, we develop a new and efficient local weighted average filter for edge-aware smoothing. The proposed filter can use guidance information which permits an iterative filtering process. Since the weights of the proposed filter depend on the local variance, the implementation requires linear filters only, leading to O(N pix ) computational complexity. We also present statistical analysis and simulations which provides new insights into its computational efficiency and its relationship with the bilateral filter. The performance of the proposed filter is comparable to those state-of-the-art filters in many applications including: edge-preserving smoothing, compression artifact removal, structure separation, edge extraction, non-photo realistic image rendering, salience detection, detail magnification and multi-focus image fusion.

ملخص البحث :

In this paper, a tracking robust sliding mode learning control (SMLC) is pro- posed for a linear motor (LM) system. The proposed controller approach, SMLC, can guarantee a zero tracking error in the absence and presence of sys- tem uncertainties of the LM system. Unlike other classical sliding mode control (CSMC), the proposed control system is designed without any prior knowledge of the system perturbation which would facilitate control design and simplify its practical applications. To this end, a recursive learning technique is used which simultaneously adapted based on the previous information of the closed loop system stability. The system stability and convergence analysis are rigorously proved in the sense of the Lybenouve criteria. Finally, simulations results are presented to demonstrate the validity and effectiveness of the SMLC over the CSMC in terms of tracking performance and chattering alleviation.

ملخص البحث :

This paper proposes a recursive sliding-mode control strategy for motion-tracking control of ionic polymer-metal composite soft actuator systems. The suggested controller is distinctive in that it can continuously modify the closed-loop response to maintain system stability. Accordingly, Lyapunov criteria have been used to establish the stability of the provided control technique. Additionally, since controller design does not require any prior knowledge of parameter uncertainties or system hysteresis, it is appropriate for ionic polymer-metal composites since its model changes depending on working conditions. Simulation investigations are conducted to validate the performance of the developed controller. The results demonstrate superior performance compared to the conventional sliding mode control approach.