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 …

The traditional K‐singular value decomposition (K‐SVD) algorithm has poor image‐
denoising performance under strong noise. An image‐denoising algorithm is proposed …

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 …

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 …

The existing image compression methods usually choose or optimize low-level
representation manually. Actually, these methods struggle for the texture restoration at low …

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 …

The problem of dictionary learning (DL) for sparse representations can be approximately
solved by several algorithms. Regularization of the optimization objective (representation …

The next generation of oil and gas exploration technology is moving toward large-scale
seismic acquisition, automation, and flexibility. This phenomenon has accelerated the …

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 …

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 …