Digital image inverse filtering for improving visual acuity for computer users with visual aberrations

Figures & data

Figure 1. Block diagram of visual system.

Figure 2. Pre-compensation process.

Figure 3. Example of an icon pre-compensated using Equation 4.

Figure 4. Not all of the information in the pre-compensated image (left) is necessary to provide an adequate retinal image (right).

Figure 5. Roberts cross–gradient operators.

Figure 6. Segmentation example.

Figure 7. Mask (IH(x, y)) to be used for extracting relevant information from the initial pre-compensated image and its edge–detected image.

Figure 8. Results of this final step, and the corresponding simulated retinal image.

Table 1. ANOVA: Data vs. R, M.

Factor	Type	Levels	Values
R	fixed	9	5, 6, 7, 8, 9, 10, 11, 12, 13
M	fixed	2	1, 2
ANOVA for Data
Source	DF	SS	MS	F	P
R	8	2452723	306590	42.61	0.000
M	1	1341269	1341269	186.41	0.000
R * M	8	169565	21196	2.95	0.007
Error	72	518064	7195
Total	89	4481620

Figure 9. Analysis of means for factor M.