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The letter addresses the image fusion problem, where multiple images captured with different focus distances are to be combined into a higher quality all-in-focus image. Most current approaches for image fusion strongly rely on the unrealistic noise-free assumption used during the image acquisition, and then yield limited fusion robustness. In our approach, we formulate the multifocus image fusion...
This paper presents a neighbourhood-based weighted super-resolution approach that estimates a high resolution video sequence from the low resolution video sequence. Firstly, In order to reduce artifacts in the super-resolved outcome due to the inaccurate estimation in the non-global motion fields, a neighbourhood-based weighted functional in terms of local mean residual is used to weight each low...
Regularization plays a vital role in ill-posed problems. A properly chosen regularization can direct the solution toward a better quality outcome. An emerging powerful regularization is one that leans on image examples. In this paper, we propose a novel scheme for face hallucination. We target specially the quality of highly zoomed outputs. Our work bases on the pyramid framework and assigns several...
Image principle component analysis (IMPCA) is a rapid direct feature extract approach from matrix. We present the basic theory of IMPCA from the view of minimizing the mean reconstruction error. We analyze the feature generated from IMPCA and find they present row characters. Wavelet transform can be used in reducing noise of images and the wavelet image should be more suitable for recognition. Our...
A novel fusion method is proposed for image sequence which based on the non-Gaussian statistical modeling of wavelet coefficients. Firstly, the source images are decomposed by dual tree complex wavelet transform (DT-CWT) respectively. Then, the wavelet coefficients are modeled using the generalized Gaussian distribution (GGD). Saliency measure, the weighted coefficient, is calculated by estimating...
This paper presents a novel enhancement filter as a preprocessing step in the early detection of lung cancer. The identification and enhancement of the nodular structures is the initial stage in computer-aided diagnosis (CAD) for improving the sensitivity of nodule detection and reducing the number of false positives. Based on nodular texture feature and mathematical morphology, our proposed enhancement...
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