Contrast Enhancement of Images on Retina by Adjusting Deconvolved Images

Zhao, Jiaxi; Liu, Lin; Zhang, Jing; Tianhe, Wang

doi:10.1109/icivc52351.2021.9526982

Cited by 2 publications

(1 citation statement)

References 10 publications

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“…Non-invasive vision-correcting devices have recently made significant progress, and vision simulation is also a crucial element for their development. Among the earliest devices to be developed, vision-correcting displays typically apply inverse blurring to the displayed imagery to compensate for the aberrations of the observer of the display [88][89][90].…”

Section: Vision-correcting Devicesmentioning

confidence: 99%

Rendering algorithms for aberrated human vision simulation

Csoba

Kunkli

2023

Vis. Comput. Ind. Biomed. Art

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Vision-simulated imagery―the process of generating images that mimic the human visual system―is a valuable tool with a wide spectrum of possible applications, including visual acuity measurements, personalized planning of corrective lenses and surgeries, vision-correcting displays, vision-related hardware development, and extended reality discomfort reduction. A critical property of human vision is that it is imperfect because of the highly influential wavefront aberrations that vary from person to person. This study provides an overview of the existing computational image generation techniques that properly simulate human vision in the presence of wavefront aberrations. These algorithms typically apply ray tracing with a detailed description of the simulated eye or utilize the point-spread function of the eye to perform convolution on the input image. Based on the description of the vision simulation techniques, several of their characteristic features have been evaluated and some potential application areas and research directions have been outlined.

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Section: Vision-correcting Devicesmentioning

confidence: 99%

Rendering algorithms for aberrated human vision simulation

Csoba

Kunkli

2023

Vis. Comput. Ind. Biomed. Art

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Fast rendering of central and peripheral human visual aberrations across the entire visual field with interactive personalization

Csoba,

Kunkli

2023

Vis Comput

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With the recent progress made in areas such as head-mounted displays and vision-correcting devices, there is a growing interest in fast and personalized algorithms for simulating aberrated human vision. Existing vision-simulating approaches are generally hindered by the lack of personalization, computational cost of rendering, and limited types of supported aberrations. This paper presents a fast vision simulation method with interactive personalization capabilities for simulating arbitrary central and peripheral aberrations of the human eye. First, we describe a novel, neural network-based solution for efficiently estimating the physical structure of the simulated eye and calculating the necessary Zernike aberration coefficients for computing the point-spread functions with varying pupil sizes, focus distances, and incidence angles. Our new approach operates in the sub-second regime and produces highly accurate outputs, facilitating the interactive personalization of vision simulation. Next, we present an improved PSF interpolation method for an existing tiled PSF splatting algorithm for rendering. The proposed algorithm significantly improves the computational performance and memory efficiency of the previous approach, allowing the simulation of peripheral vision with arbitrary visual aberrations in low-latency applications. Following the description of our new techniques, we evaluate their performance characteristics and simulation accuracies on several different eye conditions and test scenarios and compare our results to several previous vision simulation algorithms.

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Contrast Enhancement of Images on Retina by Adjusting Deconvolved Images

Cited by 2 publications

References 10 publications

Rendering algorithms for aberrated human vision simulation

Rendering algorithms for aberrated human vision simulation

Fast rendering of central and peripheral human visual aberrations across the entire visual field with interactive personalization

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