Fast multi‐spectral image super‐resolution via sparse representation
نویسندگان
چکیده
منابع مشابه
Image Classification via Sparse Representation and Subspace Alignment
Image representation is a crucial problem in image processing where there exist many low-level representations of image, i.e., SIFT, HOG and so on. But there is a missing link across low-level and high-level semantic representations. In fact, traditional machine learning approaches, e.g., non-negative matrix factorization, sparse representation and principle component analysis are employed to d...
متن کاملFace Image Superresolution via Locality Preserving Projection and Sparse Coding
It is important to enhance the resolution of face images from video surveillance for recognization and other post processing. In this paper, a novel sparse representation based face image superresolution (SR) method is proposed to reconstruct a high resolution (HR) face image from a LR observation. First, it gets a HR-LR dictionary pair for certain input LR patch via position patch clustering a...
متن کاملBlind image deblurring via coupled sparse representation
The problem of blind image deblurring is more challenging than that of non-blind image deblurring, due to the lack of knowledge about the point spread function in the imaging process. In this paper, a learningbased method of estimating blur kernel under the ‘0 regularization sparsity constraint is proposed for blind image deblurring. Specifically, we model the patch-based matching between the b...
متن کاملMultispectral Image Denoising via Nonlocal Multitask Sparse Learning
The goal of multispectral imaging is to obtain the spectrum for each pixel in the image of a scene and deliver much reliable information. It has been widely applied to several fields including mineralogy, oceanography and astronomy. However, multispectral images (MSIs) are often corrupted by various noises. In this paper, we propose a MSI denoising model based on nonlocal multitask sparse learn...
متن کاملSuperresolution Image Reconstruction Using Fast Inpainting Algorithms
The main aim of this paper is to employ the total variation (TV) inpainting model to superresolution imaging problems. We focus on the problem of reconstructing a highresolution image from several decimated, blurred and noisy low-resolution versions of the high-resolution image. We propose a general framework for multiple shifted and multiple blurred low-resolution image frames which subsumes s...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IET Image Processing
سال: 2020
ISSN: 1751-9659,1751-9667
DOI: 10.1049/iet-ipr.2019.0714