A low distortion image enhancement scheme based on multi-resolutions analysis in next generation network |
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Authors: | Jiao Feng Naixue Xiong Laurence T Yang Yan Yang |
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Affiliation: | (1) Computer and Software Institute, Nanjing University of Information Science and Technology, Nanjing, China;(2) Department of Computer Science, Georgia State University, 34 Peachtree Street, Suite 1428, Atlanta, GA 30303, USA;(3) Department of Computer Science, St. Francis Xavier University, Antigonish, Canada;(4) Department of Computer Science, Western Illinois University, Macomb, IL, USA |
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Abstract: | With the advent of Next Generation Network (NGN), services that are currently provided by multiple specific network-centric
architectures. NGN provides AAA (Anytime, Anywhere and Always on) access to users from different service providers with consistent
and ubiquitous provision of services as necessary. This special issue of NGN includes pervasive, grid, and peer-to-peer computing
to provide computing and communication services at anytime and anywhere. In fact, the application of NGN includes digital
image processing, multimedia systems/services, and so on. Here we focus on the digital image processing technology in NGN
environments. Low-contrast structure and heavy noise in NGN environments can be found in many kinds of digital images, which
makes the images vague and uncertainly, especially in x-ray images. As result, some useful tiny characteristic are weakened—which
are difficult to distinguish even by naked eyes. Based on the combination of no-linear grad-contrast operator and multi-resolution
wavelet analysis, a kind of image enhancement processing algorithm for useful tiny characters is presented. The algorithm
can enhance the tiny characters while confine amplifying noise. The analysis of the results shows that local regions of the
image are enhanced by using the concept of the grad contrast to make image clearer adaptively. Experiments were conducted
on real pictures, and the results show that the algorithm is flexible and convenient. |
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