Image Statistic Models Characterize Well Log Image Quality

Paul, Somdyuti; Bovik, Alan C.

doi:10.1109/lgrs.2019.2893363

Cited by 1 publication

(1 citation statement)

References 12 publications

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“…Natural image quality evaluator (NIQE) extracts the features in the image to test the test image. These features are fitted into a multivariate Gaussian, and the separation is normalized (Balasubramanyam Appina et al , 2019; Paul and Bovik, 2019): …”

Section: Blind Motion Deblurringmentioning

confidence: 99%

Blind image deblurring for a close scene under a 6-DOF motion path

Wang

Zhang

et al. 2021

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Purpose How to model blind image deblurring that arises when a camera undergoes ego-motion while observing a static and close scene. In particular, this paper aims to detail how the blurry image can be restored under a sequence of the linear model of the point spread function (PSF) that are derived from the 6-degree of freedom (DOF) camera’s accurate path during the long exposure time. Design/methodology/approach There are two existing techniques, namely, an estimation of the PSF and a blind image deconvolution. Based on online and short-period inertial measurement unit (IMU) self-calibration, this motion path has discretized a sequence of the uniform speed of 3-DOF rectilinear motion, which unites with a 3-DOF rotational motion to form a discrete 6-DOF camera’s path. These PSFs are evaluated through the discrete path, then combine with a blurry image to restoration through deconvolution. Findings This paper describes to build a hardware attachment, which is composed of a consumer camera, an inexpensive IMU and a 3-DOF motion mechanism to the best of the knowledge, together with experimental results demonstrating its overall effectiveness. Originality/value First, the paper proposes that a high-precision 6-DOF motion platform periodically adjusts the speed of a three-axis rotational motion and a three-axis rectilinear motion in a short time to compensate the bias of the gyroscope and the accelerometer. Second, this paper establishes a model of 6-DOF motion and emphasizes on rotational motion, translational motion and scene depth motion. Third, this paper addresses a novel model of the discrete path that the motion during long exposure time is discretized at a uniform speed, then to estimate a sequence of PSFs.

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Section: Blind Motion Deblurringmentioning

confidence: 99%

Blind image deblurring for a close scene under a 6-DOF motion path

Wang

Zhang

et al. 2021

View full text Add to dashboard Cite

show abstract

Image Statistic Models Characterize Well Log Image Quality

Cited by 1 publication

References 12 publications

Blind image deblurring for a close scene under a 6-DOF motion path

Blind image deblurring for a close scene under a 6-DOF motion path

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