Image Restoration in a Wavefront Coding Imaging System with a Wide Field of View

Feng, 周峰 Zhou; Ran, 叶然 Ye; Guangwei, 李光伟 Li; Haitao, 张海涛 Zhang; Dongsheng, 王东生 Wang

doi:10.3788/aos20103002.0388

Cited by 4 publications

(3 citation statements)

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“…The application of three rotating symmetric optical pupil masks, a single Gaussian ring mask, a multi-Gaussian ring mask, and a quadratic type phase mask, in increasing DoF is investigated in Ref. [7] and [8]. Currently, WFC systems have been used for super-resolution [9], passive ranging [10], expanding DoF [11] and so on.…”

Section: Wavefront Coding (Wfc)mentioning

confidence: 99%

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Research on an image restoration method of cubic phase plate wave-front coding with mixed noise

Zhang,

Chen,

Wang

et al. 2024

Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023)

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Wave-front coding (WFC) is a technique that adds a phase plate to an optical system's pupil exit surface. This technique first encodes the image so that the system's optical transfer function is insensitive to out-of-focus throughout a wide depth-of-focus (DoF), resulting in a blurred image. Furthermore, image noise would inevitably be generated because of device part failure or external interference. As a result, we would acquire a noisy and blurred image. The image needs to be restored to improve the imaging system's DoF. A series of experiments have been carried out to find the optimal image restoration solution. In this paper, we proposed a three-step image restoration scheme for noisy blurred images after cubic phase plate. At first, we used the Min-Max Average Pooling-based Filter (MMAPF) to remove salt-and-pepper noise. Then we used Shearlet to remove Gaussian noise. Finally, for image deblurring, we used the Amended Landweber (ALW) algorithm. Experiments on real infrared images show that this scheme has excellent performance and robustness for image restoration when applied to a cubic phase plate.

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Section: Wavefront Coding (Wfc)mentioning

confidence: 99%

“…Ref. [58] suggested a Wiener filtering-based restoration method taking into consideration the spatial variation properties of the PSF of the WFC system.…”

Section: Image Restoration Based On Wfcmentioning

confidence: 99%

Research on an image restoration method of cubic phase plate wave-front coding with mixed noise

Zhang,

Chen,

Wang

et al. 2024

Fifteenth International Conference on Graphics and Image Processing (ICGIP 2023)

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show abstract

“…Interference from the loop should be suppressed and photoelectric isolation will be used. In software, watchdog is used to prevent program running out and other measures are also taken to do data tests, data calibration, digital filtering and so on [4].…”

Section: Measures To Improve the Accuracymentioning

confidence: 99%

A New Intelligent Color Scale Sensor

Yang

Zhang

Pan

2012

AMR

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The intelligentizing of sensor has been an important trend for sensor technology in recent years. In this paper, the new structure of the intelligent color scale sensor is presented; especially the software system design of intelligent color scale sensor based on the photoelectric measurement is given in detail. By using the control system based on Micro Control Unit (MCU), which takes full advantage of the resources on MCU, a new digital intelligent color scale sensor is successfully developed at a lower cost. Also, it has an ideal performance on the key index such as sensitivity, detection accuracy, response speed, reliability, operability and degrees of protection.

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PAR Model SAR Image Interpolation Algorithm on GPU with CUDA

Yin

Fa-Long

Zhou

et al. 2014

IETE Technical Review

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Resolution of synthetic aperture radar (SAR) images is limited by imaging hardware. To improve SAR image resolution, interpolation needs to be carried out on a SAR image. An image interpolation algorithm with a good effect incurs a high computational cost and cannot be used in a real-time scenario. This paper applies Compute Unified Device Architecture (CUDA) to speed up the piece-wise autoregressive model image interpolation algorithm for acquiring high-quality SAR images. A partial differential is used to carry out image denoising. After de-noising, divide the image interpolation based on a local window of a piece-wise autoregressive model: the SAR image is first divided into many 9 £ 9 small local windows. For each window, a CUDA thread is launched to interpolate using the autoregressive interpolation algorithm. Gradient descent algorithm is used to estimate parameters of the autoregressive model in the first-and second-round interpolation. Numerical simulation indicates that this GPU-based parallel algorithm can interpolate a 2592 £ 1944 image within 1/110th of the time used by a CPU-based serial algorithm. Moreover, the computation time saved increases with the image size. The experimental results show that the method in this paper can achieve high-quality image interpolation in a low computation time.

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Image Restoration in a Wavefront Coding Imaging System with a Wide Field of View

Cited by 4 publications

References 0 publications

Research on an image restoration method of cubic phase plate wave-front coding with mixed noise

Research on an image restoration method of cubic phase plate wave-front coding with mixed noise

A New Intelligent Color Scale Sensor

PAR Model SAR Image Interpolation Algorithm on GPU with CUDA

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