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Conference on Multimedia on Mobile Devices and Multimedia Content Access - Algorithms and Systems V

作者： Nercessian, Shahan Agaian, Sos S. Panetta, Karen A. Tufts Univ Dept Elect & Comp Engn 161 Coll Ave Medford MA 02155 USA

ISBN: (纸本)9780819484185

image fusion is the effective combination of multiple images into a single fused image. The goal of the fusion is use the similar and complementary information of the source images in order to obtain an informative depiction of the scene for further processing. Many multi-scale image fusion algorithms have been formulated on the basis that the human visual system is sensitive to edge information. However, these algorithms make use of standard mathematical operators, which do not reflect human visual system characteristics over a large range of background luminance intensities. Accordingly, this paper proposes new image fusion algorithms using a new parameterized logarithmic Stationary Wavelet Transform (PL-SWT), which combines the advantages of the Stationary Wavelet Transform (SWT) and the parameterized logarithmic image processing (PLIP) model, a parameterized framework for processing images. An analysis of the PLIP model shows that it is capable of providing a balance between logarithmic and standard mathematical operators based on image dependent characteristics. Consequently, the use of the parameterized model is extended for to both pixel- and region-based fusion approaches. Experimental results via computer simulation illustrate the improved performance of the proposed image fusion algorithms by both qualitative and quantitative means.

关键词： image fusion Stationary Wavelet Transform parameterized logarithmic image processing

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logarithmic Edge Detection with Applications

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JOURNAL OF COMPUTERS 2008年第9期3卷 11-19页

作者： Panetta, Karen A. Wharton, Eric J. Agaian, Sos S. Tufts Univ Elect & Comp Engn Medford MA 02155 USA Tufts Univ SIMLAB Medford MA 02155 USA Univ Texas San Antonio Coll Engn San Antonio TX USA

In real world machine vision problems, numerous issues such as variable scene illumination make edge and object detection difficult. There exists no universal edge detection method which works well under all conditions. In this paper, we propose a logarithmic edge detection method based on parameterized logarithmic image processing (PLIP) and a four-directional Sobel method, achieving a higher level of independence from scene illumination. We present experimental results for this method, and compare results of the algorithms against several leading edge detection methods, such as Sobel and Canny. To compare results objectively, we use Pratt's Figure of Merit. We demonstrate the application of the algorithm in conjunction with Edge Preserving Contrast Enhancement (EPCE), which is an image enhancement method dependent on the raw output of an edge detection kernel. This shows that the use of this edge detection algorithm results in better image enhancement, as quantified by the logarithmic AME.

关键词： parameterized logarithmic image processing Edge Detection image Enhancement Measure of Enhancement

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Generalized Phi Number System and its Applications for image Decomposition and Enhancement

Generalized Phi Number System and its Applications for Image...

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Conference on Multimedia on Mobile Devices and Multimedia Content Access - Algorithms and Systems V

作者： Agaian, Sarkis Zhou, Yicong Stanford Univ Dept Elect Engn Stanford CA 94305 USA Interdisciplinary Solut LLC San Antonio 78215 TX USA

ISBN: (纸本)9780819484185

Technologies and applications of the field-programmable gate array (FPGAs) and digital signal processing (DSP) require both new customizable number systems and new data formats. This paper introduces a new class of parameterized number systems, namely the generalized Phi number system (GPNS). By selecting appropriate parameters, the new system derives the traditional Phi number system, binary number system, beta encoder, and other commonly used number systems. GPNS also creates new opportunities for developing customized number systems, multimedia security systems, and image decomposition and enhancement systems. A new image enhancement algorithm is also developed by integrating the GPNS-based bit-plane decomposition with parameterized logarithmic image processing (PLIP) models. Simulation results are given to demonstrate the GPNS's performance.

关键词： Number system Rational number system Phi number system parameterized logarithmic image processing Bit-plane decomposition image enhancement

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An image Contrast Enhancement Algorithm Using PLIP-based Histogram Modification 3

An Image Contrast Enhancement Algorithm Using PLIP-based His...

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3rd IEEE International Conference on Cybernetics (CYBCONF)

作者： Zhao, Zhou Zhou, Yicong Univ Macau Dept Comp & Informat Sci Macau Peoples R China

ISBN: (纸本)9781538622018

Contrast enhancement is an important tool for producing informative and visually pleasing images. However, conventional image contrast enhancement methods often suffer from the drawback of excessive enhancement. In this paper we propose a new image contrast enhancement algorithm. It embeds PLIP operations into a robust histogram modification framework. Experimental results demonstrate that the proposed algorithm can effectively enhance image contrast while preventing excessive enhancement.

关键词： contrast enhancement parameterized logarithmic image processing histogram modification

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Comparative Study of logarithmic image processing Models for Medical image Enhancement

Comparative Study of Logarithmic Image Processing Models for...

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IEEE International Conference on Systems, Man, and Cybernetics (SMC)

作者： Zhao, Zhou Zhou, Yicong Univ Macau Dept Comp & Informat Sci Macau Peoples R China

ISBN: (纸本)9781509018970

Medical image enhancement is an effective tool to improve visual quality of digital medical images. However, conventional linear image enhancement methods often suffers from problems such as over-enhancement and noise sensitivity. In this paper, we study nonlinear arithmetic frameworks designed to solve the common problems of linear enhancement methods, namely, LIP, PLIP and GLIP. We also introduce nonlinear unsharp masking algorithms based on the logarithmic image processing models for medical image enhancement. Experiments are conducted to evaluate and compare the performance of the methods.

关键词： medical image enhancement unsharp masking logarithmic image processing parameterized logarithmic image processing generalized logarithmic image processing

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