[图书][B] Dictionary learning algorithms and applications
B Dumitrescu, P Irofti - 2018 - Springer
This book revolves around the question of designing a matrix D∈ Rm× n called dictionary,
such that to obtain good sparse representations y≈ Dx for a class of signals y∈ Rm given …
such that to obtain good sparse representations y≈ Dx for a class of signals y∈ Rm given …
Image‐denoising algorithm based on improved K‐singular value decomposition and atom optimization
R Chen, D Pu, Y Tong, M Wu - CAAI Transactions on …, 2022 - Wiley Online Library
The traditional K‐singular value decomposition (K‐SVD) algorithm has poor image‐
denoising performance under strong noise. An image‐denoising algorithm is proposed …
denoising performance under strong noise. An image‐denoising algorithm is proposed …
Quaternion-based dictionary learning and saturation-value total variation regularization for color image restoration
Color image restoration is a critical task in imaging sciences. Most variational methods
regard the color image as a Euclidean vector or the direct combination of three monochrome …
regard the color image as a Euclidean vector or the direct combination of three monochrome …
Sim-to-Real: Employing ultrasonic guided wave digital surrogates and transfer learning for damage visualization
Wavefield imaging is a powerful visualization tool in nondestructive evaluation for studying
ultrasonic wave propagation and its interactions with damage. To isolate and study damage …
ultrasonic wave propagation and its interactions with damage. To isolate and study damage …
Semantic perceptual image compression with a Laplacian pyramid of convolutional networks
The existing image compression methods usually choose or optimize low-level
representation manually. Actually, these methods struggle for the texture restoration at low …
representation manually. Actually, these methods struggle for the texture restoration at low …
Classification of diabetic retinopathy using unlabeled data and knowledge distillation
Over the last decade, advances in Machine Learning and Artificial Intelligence have
highlighted their potential as a diagnostic tool in the healthcare domain. Despite the …
highlighted their potential as a diagnostic tool in the healthcare domain. Despite the …
Regularized k-svd
B Dumitrescu, P Irofti - IEEE Signal Processing Letters, 2017 - ieeexplore.ieee.org
The problem of dictionary learning (DL) for sparse representations can be approximately
solved by several algorithms. Regularization of the optimization objective (representation …
solved by several algorithms. Regularization of the optimization objective (representation …
Advances in seismic data compression via learning from data: Compression for seismic data acquisition
The next generation of oil and gas exploration technology is moving toward large-scale
seismic acquisition, automation, and flexibility. This phenomenon has accelerated the …
seismic acquisition, automation, and flexibility. This phenomenon has accelerated the …
[PDF][PDF] 基于Boosting 回归的单帧图像超分辨率重建
罗爽, 黄辉, 张凯兵 - Laser & Optoelectronics Progress, 2022 - researching.cn
摘要实例学习是一种有效的单帧图像超分辨率重建技术, 关键在于如何建立低分辨率与高分辨率
图像之间的映射关系. 许多研究表明, 当面对复杂多样的自然图像时, 类型单一的回归模型难以 …
图像之间的映射关系. 许多研究表明, 当面对复杂多样的自然图像时, 类型单一的回归模型难以 …
Histogram alternation based digital image compression using base-2 coding
The intention of data compression is to promote the storage and delivery of big images with
excellent compression ratio and least distortion. Moreover, the number of internet user is …
excellent compression ratio and least distortion. Moreover, the number of internet user is …