Joint Motion Deblurring with Blurred/Noisy Image Pair

Author(s):  
Haisen Li ◽  
Yanning Zhang ◽  
Jinqiu Sun ◽  
Dong Gong
2012 ◽  
Vol 285 (7) ◽  
pp. 1777-1786 ◽  
Author(s):  
Ser-Hoon Lee ◽  
Hyung-Min Park ◽  
Sun-Young Hwang

2021 ◽  
Vol 30 ◽  
pp. 345-359
Author(s):  
Chunzhi Gu ◽  
Xuequan Lu ◽  
Ying He ◽  
Chao Zhang
Keyword(s):  

2013 ◽  
Vol 24 (8) ◽  
pp. 1303-1315 ◽  
Author(s):  
Chang-Hwan Son ◽  
Hyunseung Choo ◽  
Hyung-Min Park

2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Linyang He ◽  
Gang Li ◽  
Jinghong Liu

Currently superresolution from a motion blurred image still remains a challenging task. The conventional approach, which preprocesses the blurry low resolution (LR) image with a deblurring algorithm and employs a superresolution algorithm, has the following limitation. The high frequency texture of the image is unavoidably lost in the deblurring process and this loss restricts the performance of the subsequent superresolution process. This paper presents a novel technique that performs motion deblurring and superresolution jointly from one single blurry image. The basic idea is to regularize the ill-posed reconstruction problem using an edge-preserving gradient prior and a sparse kernel prior. This method derives from an inverse problem approach under an efficient optimization scheme that alternates between blur kernel estimation and superresolving until convergence. Furthermore, this paper proposes a simple and efficient refinement formulation to remove artifacts and render better deblurred high resolution (HR) images. The improvements brought by the proposed combined framework are demonstrated by the processing results of both simulated and real-life images. Quantitative and qualitative results on challenging examples show that the proposed method outperforms the existing state-of-the-art methods and effectively eliminates motion blur and artifacts in the superresolved image.


1998 ◽  
Vol 3 (5) ◽  
pp. 4-5
Author(s):  
Christopher R. Brigham

Abstract Accurate measurement of shoulder motion is critical in assessing impairment following shoulder disorders. To this end, measuring and recording joint motion are important steps in diagnosing, determining the severity and progression of a disorder, assessing the results of treatment, and evaluating impairment. Shoulder movement usually is composite rather than in a single plane, so isolating single movements is challenging. Universal goniometers with long arms are used to measure shoulder motion, and testing must be performed and recorded consistently. Passive motion may be carried out cautiously by the examiner; two measurements of the same patient by the same examiner should lie within 10° of each other. Shoulder extension and flexion are illustrated. Maximal flexion of the shoulder also includes slight external rotation and abduction, and controlling or eliminating these components during evaluation is challenging. Abduction and adduction are illustrated. Deficits in external rotation may occur in patients who have undergone reconstructive procedures with an anterior approach; deficits in internal rotation may result from issues with shoulder instability. The authors recommend recording the shoulder's range of motion measurements according to the Upper Extremity Impairment Evaluation Record in the AMA Guides to the Evaluation of Permanent Impairment, Fourth Edition.


Sign in / Sign up

Export Citation Format

Share Document