Sparse representation and variational methods in retinal image processing. In: Intern. Fed. for Medical & Biological Engineering. Springer Proceedings Series. 26th Southern Biomedical Engineering Conference; 2010. p. 361–365.Dobrosotskaya, J., Ehler, M., et al.: Sparse representation and ...
B. 图像处理中的稀疏表示(SPARSE REPRESENTATION IN IMAGE PROCESSING) C. 图像分类和视觉跟踪中的稀疏表示(SPARSE REPRESENTATION IN IMAGE CLASSIFICATION AND VISUAL TRACKING) IX. 实验评价(EXPERIMENTAL EVALUATION) A. 参数选择(PARAMETER SELECTION) Parameter selection, especially selection of the regularization para...
Advances in Imaging and Electron PhysicsVelisavljevic V,Vetterli M,Beferull L B.Sparse image representation by directionlets. Advances in Imaging and Electron Physics . 2010Velisavljevic V, Vetterli M, and Beferull L B. Sparse image representation by directionlets [J]. Advances in Imaging and ...
a general framework for image fusion based on multi-scale transform and sparse representation:基于多尺度变换和稀疏表示的图像融合总体框架 热度: 相关推荐 Sparseapproximationsinimageprocessing AnnaC.Gilbert DepartmentofMathemtics UniversityofMichigan Basicimagecompression:transformcoding Tutorialonsparseapproximati...
Therefore, the sparse representation of a low resolution image patch can be applied with the high resolution image patch dictionary to generate a high resolution image patch. The learned dictionary pair is a more compact representation of the patch pairs, compared to previous approaches, which ...
Sparse representationFace imageImage qualityDiscrete wavelet transformIncreasing the quality of low-resolution images, namely super-resolution, has recently received a lot of attention in the field of image processing. Super-resolution has various applications,......
sparse representation, the ssim index is used for a criterion to optimize the representation performance. specifically, the proposed method introduces the ssim-based criterion into two important procedures in the sparse representation problem, i.e., 'estimation of the sparse representation coefficients’...
As an emerging field in signal processing, sparse representation often appears together with the concept of compressed sensing. Compressed sensing is a kind of method proposed to break through the Nyquist rate in Shannon sampling theorem. It aims to improve the sampling efficiency by finding the key...
This paper presents an image inpainting method based on sparse representations optimized with respect to a perceptual metric. In the proposed method, the structural similarity (SSIM) index is utilized as a criterion to optimize the representation performance of image data. Specifically, the proposed me...
Sparse representation Deep learning Super-resolution Feature fusion 1. Introduction The vision is the primary path for human to obtain information, and the effect of vision information mostly dependents on the quality of the image. The most important index to measure the quality of the image is sp...