In this paper we present a novel image decomposition method via credible data fitting with local total variation filter. The oscillation rate is used to measure the image complexity and characteristics. The filter parameter can be determined by a fitting curve which is reconstructed by oscillation rate. In addition, the approximate Gaussian algorithm and integral image are used to reduce the algorithm computation and the sensitivity of the filter window selection. Experiments show the new method is better than the exist- ing methods.
Energy minimization has been widely used for constructing curve and surface in the fields such as computer-aided geometric design, computer graphics. However, our testing examples show that energy minimization does not optimize the shape of the curve sometimes. This paper studies the relationship between minimizing strain energy and curve shapes, the study is carried out by constructing a cubic Hermite curve with satisfactory shape. The cubic Hermite curve interpolates the positions and tangent vectors of two given endpoints. Computer simulation technique has become one of the methods of scientific discovery, the study process is carried out by numerical computation and computer simulation technique. Our result shows that： （1） cubic Hermite curves cannot be constructed by solely minimizing the strain energy; （2） by adoption of a local minimum value of the strain energy, the shapes of cubic Hermite curves could be determined for about 60 percent of all cases, some of which have unsatisfactory shapes, however. Based on strain energy model and analysis, a new model is presented for constructing cubic Hermite curves with satisfactory shapes, which is a modification of strain energy model. The new model uses an explicit formula to compute the magnitudes of the two tangent vectors, and has the properties： （1） it is easy to compute; （2） it makes the cubic Hermite curves have satisfactory shapes while holding the good property of minimizing strain energy for some cases in curve construction. The comparison of the new model with the minimum strain energy model is included.
LI Xue-meiZHANG Yong-xiaMA LongZHOU Yuan-fengZHANG Cai-ming
Image enhancement plays an important role in many applications of medical imaging. Image enhancement technologies can improve the qualities of medical images with low contrast and high level noise by stretching contrast, suppressing noise and so on. Such images processed by image enhancement technologies are helpful to doctors in analyses and diagnoses. In this paper, we present a technical review of various existing image enhancement methodologies which are often emoloved.
Point-based surface has been widely used in computer graphics for modeling, animation, visualization, simulation of liq- uid and so on. Furthermore, particle-based approach can distribute the surface sampling points and control its parameters according to the needs of the application. In this paper, we examine several kinds of algorithms presented over the last decades, with the main focus on particle sampling technologies for implicit surface. Therefore, we classify various algorithms into categories, describe main ideas behind each categories, and compare the advantages and shortcomings of the algorithms in each category.
This paper proposes a novel method for image magnification by exploiting the property that the intensity of an image varies along the direction of the gradient very quickly. It aims to maintain sharp edges and clear details. The proposed method first calculates the gradient of the low-resolution image by fitting a surface with quadratic polynomial precision. Then,bicubic interpolation is used to obtain initial gradients of the high-resolution(HR) image. The initial gradients are readjusted to find the constrained gradients of the HR image, according to spatial correlations between gradients within a local window. To generate an HR image with high precision, a linear surface weighted by the projection length in the gradient direction is constructed. Each pixel in the HR image is determined by the linear surface. Experimental results demonstrate that our method visually improves the quality of the magnified image. It particularly avoids making jagged edges and bluring during magnification.
In CAGD and CG, energy model is often used to control the curves and surfaces shape. In curve/surface modeling, we can get fair curve/surface by minimizing the energy of curve/surface. However, our research indicates that in some cases we can＇t get fair curves/surface using the current energy model. So an improved energy model is presented in this paper. Examples are also included to show that fair curves can be obtained using the improved energy model.
In this paper we present a new image zooming algorithm based on surface fitting with edge constraint. In surface fitting,we consider not only the relationship of corresponding pixels between the original image and the enlarged image, but also the neighbor pixels in the enlarged image according to the local structure of original image. Furthermore, during surface fitting, more interpolation constraints are used in the new algorithm for improving the precision of the super sampling pixels. The experimental results show that the new method outperforms the previous methods which based on surface fitting.
GUO YingyingZHANG CaimingLI WeitaoZHOU YuanfengWANG Min
