Optical Veiling Glare and Neural Processing:
Spatial Partners in Vision

 
 

Frontiers Research Topic

in Psychology - Perception Science


Imaging is the integration of optics and light sensing in both vision and scene reproduction. Optics makes the capture of scene radiances possible, but introduces limits to the quality of captured information in both resolution and dynamic range. This Frontiers Topic invites papers from all related research.

Simply stated, our eyes form an image on our retinas that is sensed by our nervous system. As well, cameras capture scene radiances and reproduce scenes for human viewing and computer analysis. While resolution is used as a primary measure of image quality (20/20 vision & number of camera pixels) the range of light is profoundly influenced by both optical glare and scene content. Every optical system scatters a very small amount of light from each “pixel” * onto every other pixel.  Glare is the sum of all the small contributions from all the other pixels.  If the scene is limited to a tiny spot of light in a no light background, then glare is vanishingly small because nearly all pixels make zero contribution to glare.  If the scene is a white sandy beach, then nearly every pixel makes a maximal contribution to scene dependent glare. Glare controls the range of light falling on image sensors in vision and reproduction.

The role of glare, particularly its variability with scene content, is fundamental to our understanding of vision and reproduction. It becomes more interesting when we consider that post-visual pigment neural processes in human vision act to counteract the effects of glare. Experiments have calculated all radiance values for different retinal images having variable scene content. The resulting plots of retinal radiance vs. apparent lightness vary markedly with scene content. Vision and visual reproduction need to be studied with the light on the sensor, rather than light from the scene.

This Frontiers Research topic goes beyond Glare to encompass experiments that study why glare is not obvious in everyday life. Human vision does a remarkable job of reducing the visibility of glare. When we understand these mechanisms, we will be able to apply human-glare-processing  principles to photography and computer vision.

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  1. *In this description “pixel” is used as a generic term to mean a small sector of a silicon sensor in cameras, and a small region of the retina in vision.



Interdisciplinary Study of Glare


Current research on related parts of Glare in imaging


  1. 1.  Human Glare Spread Function (GSF)

         - Characterization of ocular glare:

  1. a. The Effects of Glare

  2. b. CIE Standard Glare Observer

  3. c.  Retinal Point Spread Function

  4. d.  Scene vs. Retinal Luminances

  5. e.  Calculating the Retinal Image

                     SEE REVIEW: Human Glare Spread Function


  1. 2.  Camera Glare Spread Function (GSF)

         - Characterization of optical glare:

  1. a.  Camera Optics

  2. b.  ISO Glare Standard

  3.               SEE REVIEW: Camera Glare Spread Function


  1. 3. Human Response Function (HSF) - Human Psychophysics

         -Result vary with Scene Content

  1. a. Human response to light:

    intraocular glare and post-receptor neural processing     

  1. b.  Glare Influences the HRF

  2. c.  The RETINAL Response to Light

  3. d.  Human Response Model

  4. e.  Spatial vs. Pixels-based Algorithms

                    SEE REVIEW: Glare and Scene Content


    4.  Headlight Glare

    1. a.  Importance of the problem

    2. b.  Cataract 

    3. c.  Glare and night driving

  1.                     SEE REVIEW: Headlight Glare


    5.  Glare in Photography

  1. a. The Role of Scene Content

  2. b. Glare in Low-Dynamic-Range Scenes

         SEE REVIEW: Glare in Photography


    6.  Glare in Reproduction

    1. a.  Three HDR Techniques

    2. b.  Painting

    3. c.  Photography

    4. d.  Electronic Imaging

  1.                   SEE REVIEW: Glare in Reproduction


  1. 7.Standard sRGB vs. RAW format

  2.       a.  Color Space

  3.       b.  Is Chromaticity the signature of reflectance?        

                     SEE REVIEW: Standard sRGB vs. RAW format

         

    8.  Glare in Computer Vision


                    SEE REVIEW: Glare in Computer Vision