The long-term goal of this project is to design and evaluate practical image enhancement methods that would enable people with impaired vision, particularly those with central field loss due to age-related macular disease, to enjoy and benefit from the spread of video technology. Towards this goal, we are developing enhancement methods and investigating factors affecting patient performance with, and the appearance of, enhanced images. Our work is guided by our evolving vision model of contrast perception that we (and others) use in developing, testing, and refining image enhancement techniques. We believe that a basic understanding of contrast and image perception is essential for progress in this area, and that our clinical and basic research efforts usefully interact with each other in ways that benefit both. In this proposal we emphasize more-directly-applicable aspects of the project by developing new ways to measure preference and perceived image quality for video sequences, and by evaluating improved and new enhancement algorithms. We continue our investigation of form vision in patients with central field loss and of the possible role of brain plasticity in this process. We also continue to investigate the possible impact of short-term adaptations to blur and sharpness in reducing the perceived improvement of perception with enhancements, and possible ways to counter these effects. Specifically, we will evaluate the properties of our new method for measuring instantaneous image quality in motion videos and its value in studying image enhancement as well as the image degradation caused by digital compression. We will implement and evaluate a method of pairwise comparison to quantify preferences for enhancement, and apply these evaluation techniques in the selection of enhancement parameters and assessment of image quality. We will evaluate: our adaptive enhancement algorithm (as implemented on an inexpensive consumer product), an improved nonlinear version of that algorithm, and an enhancement for digital video designed to work directly in the compression (MPEG) domain. We will also evaluate the benefit of newly-available high brightness and high dynamic range displays. We will continue our psychophysical studies, in an effort to understand the adaptations and changes that affect patients who lose their central retina.

Public Health Relevance

A growing number of Americans suffer from disabling age-related visual impairments. Access to the growing flow of video images presented on the screens of TVs, computers, and hand-held devices is important as a means for obtaining information and sharing in the culture of our society. The goal of this project is to design and evaluate practical image enhancement methods that would allow people with impaired vision - particularly those with age related macular disease - to enjoy and benefit from the spread of video technology.

National Institute of Health (NIH)
National Eye Institute (NEI)
Research Project (R01)
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Special Emphasis Panel (ZRG1-ETTN-R (92))
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Wiggs, Cheri
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Schepens Eye Research Institute
United States
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Vera-Diaz, Fuensanta A; Woods, Russell L; Peli, Eli (2017) Blur Adaptation to Central Retinal Disease. Invest Ophthalmol Vis Sci 58:3646-3655
Jung, Jae-Hyun; Pu, Tian; Peli, Eli (2016) Comparing object recognition from binary and bipolar edge images for visual prostheses. J Electron Imaging 25:
Jung, Jae-Hyun; Pu, Tian; Peli, Eli (2016) Comparing object recognition from binary and bipolar edge features. IS&T Int Symp Electron Imaging 2016:
Jung, Jae-Hyun; Aloni, Doron; Yitzhaky, Yitzhak et al. (2015) Active confocal imaging for visual prostheses. Vision Res 111:182-96
Radhakrishnan, Aiswaryah; Sawides, Lucie; Dorronsoro, Carlos et al. (2015) Single neural code for blur in subjects with different interocular optical blur orientation. J Vis 15:15
Haun, Andrew M; Peli, Eli (2015) Similar Sensitivity to Ladder Contours in Macular Degeneration Patients and Controls. PLoS One 10:e0128119
García-Pérez, Miguel A; Peli, Eli (2015) Aniseikonia Tests: The Role of Viewing Mode, Response Bias, and Size-Color Illusions. Transl Vis Sci Technol 4:9
Hwang, Alex D; Peli, Eli (2014) An augmented-reality edge enhancement application for Google Glass. Optom Vis Sci 91:1021-30
Haun, Andrew M; Peli, Eli (2014) Binocular rivalry with peripheral prisms used for hemianopia rehabilitation. Ophthalmic Physiol Opt 34:573-9
Dilks, Daniel D; Julian, Joshua B; Peli, Eli et al. (2014) Reorganization of visual processing in age-related macular degeneration depends on foveal loss. Optom Vis Sci 91:e199-206

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