Nowadays deep learning-based models have made encouraging accomplishments in the field of image motion deblurring, but this type of algorithms does not effectively use the known prior knowledge and the physical model of motion blur. So as to settle the above disputes, this paper suggests a multi-patch multi-scale input model that fuses high-frequency information, structural self-similarity (SSS), multi-scale channel spatial attention (MSCSA), and superpixel gradient loss for motion deblurring. The multi-patch multi-scale input model can fully extract the salient information, scale information, and high-frequency information of the image to restore the sharp image. The SSS module can take full advantage of the prior information of the structure selfsimilarity of the image. And the MSCSA module dynamically and selectively enhances relevant features and suppresses irrelevant features by fusing spatial, scale, and channel characteristics. Moreover, this paper advises a superpixel gradient loss function, which can remove motion blur and restore sharp images more effectively. And to increase the diversity of scenes, for the first time, we propose a motion blur dataset (Underwater-Blur) specifically for underwater scenes. Massive comparative experiments conducted on three public datasets of GoPro, RealBlur, RWBI, and the Underwater-Blur dataset prove that our model outperforms the state-of-the-art in terms of comprehensive performance.

Nianzu Qiao

Jia Sun

Duo Xu

Changyin Sun

Computer Vision and Image Understanding

该杂志的中心焦点是图片信息的计算机分析。计算机视觉和图像理解发表的论文涵盖了图像分析的各个方面，从早期视觉的低级标志性过程到识别和解释的高级象征性过程。涵盖了图像理解领域的广泛主题，包括提供与主流观点不同的见解的论文。研究领域包括：• 理论• 早期视觉• 数据结构和表示• 形状• 范围• 运动• 匹配和识别• 建筑和语言• 视觉系统

The journal "Computer Vision and Image Understanding" focuses on the computer analysis of image information. It publishes papers covering various aspects of image analysis, ranging from low-level feature processing in early vision to high-level symbolic processes of recognition and interpretation. The topics covered are broad and include, but are not limited to: theory, early vision, data structures and representations, shape, depth, motion, matching and recognition, architecture and language, and visual systems.

《Computer Vision and Image Understanding》杂志专注于图像信息的计算机分析。该杂志发表的论文涵盖了图像分析的各个方面，从早期视觉的低级特征处理到高级的识别与解释过程。研究主题广泛，包括但不限于：理论、早期视觉、数据结构与表示、形状、深度、运动、匹配与识别、建筑与语言以及视觉系统。

Category	Quartile
计算机科学	3
计算机科学, 计算机人工智能	3
计算机科学, 工程电子与电气	3

Multi-patch multi-scale model for motion deblurring with high-frequency information

ivySCI AI Smartly Parses PDF, Answers Researchers' Questions, and Helps You Understand Papers in Seconds

Journal Info

Category	Quartile
ENGINEERING, ELECTRICAL & ELECTRONIC	1