The overall goal of this software program is to simulate the effects of adaptation on visual perception by using a model of how the human visual system adapts to encode color. This model calculates how that encoding changes when the same observer is adapted to different color environments, or when different observers are adapted to the same environment. This method addresses key questions in cognitive science and neuroscience, such as why sensory systems adapt and what effects adaptation has on perception.
The main advantage of this technique is that it incorporates plausible assumptions about adaptation and color vision and uses these to more reliably predict color perception across different environments and observers. Begin by selecting the desired image to work with and observe it pop up in the upper left pane. Then, click the format menu to choose how to represent the image and the observer.
Click on standard observer to model a standard or average observer adapting to a specific color distribution. Next, click on Natural Spectra or RGB to approximate actual light spectra or the red, green, blue pixel spectra of the image on the monitor. Begin by adapting the same observer to different environments, such as the colors of the current image versus the color distribution typical of a natural outdoor environment.
To set these environments, select the reference and test environments from the dropdown menus;then click the reference menu to choose the starting environment, which is the environment the observer is assumed to be adapted to while viewing the original image. Next, click the test menu to choose the new environment that the observer will become adapted to. Click the Adapt button and observe two new images filtered for cone adaptation and adapted for contrast adaptation.
Alternatively, to adapt different observers to the same environment, such as the spectral sensitivity of a younger or older observer;select the spectral sensitivity of the observer and click on the lens menu to choose the density of the lens pigment. Then, click on the macular menu to similarly select the density of the macular pigment;and click on the Cones menu to choose between observers with normal trichromacy or different types of anomalous trichromacy. Again, click the Adapt button and observe three new images on the screen, this time showing the original image, the image filtered for the new sensitivity, and the image after adapting to the new sensitivity.
Finally, click the Save Images button to save the three images. This protocol demonstrates how the effects of visual adaptation to a change in the environment or the observer can be visualized in images. As an illustration of how adaptation adjusts to the changes in the observer, the model simulated the consequences of lens aging by comparing the predicted appearance of an image as seen through the eyes of a younger or older observer who differ only in the density of the lens pigment.
As an illustration of how adaptation adjusts to a change in the environment, the model was used to simulate how we might adapt to a low contrast, hazy environment by adjusting color coding to match the encoding expected for a typical higher contrast environment. This technique can be applied to any image ensembles or observers with different spectral sensitivities. It can also be generalized to examine adaptation and other characteristics of images, such as their spectral properties.
The rendered images model the theoretical limits of long-term adaptation and can be used to examine the function of adaptation by testing what subjects could perceive in the adapted images that they could not perceive in the original images. The rendered images also provide more realistic simulations of the effects of the sensitivity change on our visual perception and show how adaptation tends to discount or compensate for these sensitivity changes.
