Contrast enhancement technique based on local detection of edges
Computer Vision, Graphics, and Image Processing
Ten lectures on wavelets
Contrast enhancement using the Laplacian-of-a-Gaussian filter
CVGIP: Graphical Models and Image Processing
Wavelets and subband coding
Multisensor image fusion using the wavelet transform
Graphical Models and Image Processing
Enhancement by multiscale nonlinear operators
Handbook of medical imaging
Edge detection by scale multiplication in wavelet domain
Pattern Recognition Letters
A Hybrid IMM/SVM Approach for Wavelet-Domain Probabilistic Model Based Texture Classification
WACV-MOTION '05 Proceedings of the Seventh IEEE Workshops on Application of Computer Vision (WACV/MOTION'05) - Volume 1 - Volume 01
A License Plate-Recognition Algorithm for Intelligent Transportation System Applications
IEEE Transactions on Intelligent Transportation Systems
Contrast enhancement using brightness preserving bi-histogram equalization
IEEE Transactions on Consumer Electronics
Adaptive wavelet thresholding for image denoising and compression
IEEE Transactions on Image Processing
Image quality assessment: from error visibility to structural similarity
IEEE Transactions on Image Processing
Image and Texture Segmentation Using Local Spectral Histograms
IEEE Transactions on Image Processing
IEEE Transactions on Image Processing
A Discriminative Approach for Wavelet Denoising
IEEE Transactions on Image Processing
Wavelets, Ridgelets, and Curvelets for Poisson Noise Removal
IEEE Transactions on Image Processing
Image Denoising Using Derotated Complex Wavelet Coefficients
IEEE Transactions on Image Processing
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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.