Method for filter selection

1. A method implemented by computer means of selecting an optical filtration of an ophthalmic device for a wearer, the method comprising:

obtaining wearer's preferences relative to at least one predetermined type of visual environment and taking multispectral or hyper spectral data relative to the wearer's preferences; and

selecting at least one filter:

corresponding to said wearer's preferences relative to said at least one predetermined type of visual environment, and

determined on the basis of said multispectral or hyper spectral data,

wherein said obtained wearer's preferences are obtained by at least one sensor configured to sense environment light signals; and

wherein said at least one sensor comprises a camera to acquire at least one current image comprising a multiplicity of successive lines, light signals in each band of wavelength, and in each line of said current image being measured, to generate a matrix of spatial and spectral data corresponding to same multispectral and/or hyper spectral data.

2. The method according to claim 1 , wherein said selecting of at least one filter takes into account the spectral sensitivity of the wearer.

3. The method according to claim 1 , wherein said ophthalmic device comprises an electrically commanded cell, and wherein the method further comprises commanding said electrically commanded cell to apply said selected filter.

4. The method according to claim 1 , wherein the method further comprises:

generating images representing said at least one predetermined type of visual environment of the wearer with said at least one filter applied; and

receiving a wearer input to validate based on said generated images said at least one filter selected.

5. The method according to claim 4 , wherein said generated images are displayed on a RGB (Red Green Blue) color display, and wherein said generated images are further based on spectral transmission of said at least one filter applied and on said multispectral or hyper spectral data.

6. The method according to claim 1 , wherein said at least one sensor configured to sense environment light signals is embedded in an external device or in said ophthalmic device.

7. The method according to claim 1 , wherein said at least one sensor comprises a camera and said selecting of the at least one filter comprises a predetermined pattern recognition and a selection of an adapted filtration to be applied to images acquired by the camera comprising said predetermined pattern.

8. The method according to claim 1 , wherein said obtained wearer's preferences are obtained in real time.

9. The method according to claim 3 , wherein the ophthalmic device comprises a connection to a user interface, wherein said wearer's preferences comprise data input by the wearer through said user interface when the wearer wears the ophthalmic device and is within a learning visual environment, and wherein said obtaining wearer's preferences comprises:

according to said learning visual environment, commanding the cell to apply a predetermined filter;

activating said user interface to receive from the wearer a choice input of keeping or adjusting the predetermined filter;

if said choice input is to keep said predetermined filter, storing the data of said predetermined filter in association with data acquired from the learning visual environment in a filter database assigned to said wearer; and

if said choice input is to adjust said predetermined filter, modifying the predetermined filter according to the learning visual environment and the above operations are repeated with the thus adjusted filter as a new predetermined filter.

10. The method according to claim 3 , further comprising:

providing a filter database assigned to said wearer and storing data of prerecorded filters respectively associated with data acquired from a plurality of learning visual environments;

wherein said selecting of at least one filter to be applied by the electrically commanded cell comprises:

comparing data acquired from said at least one predetermined type of visual environment successively to said data acquired from a plurality of learning visual environments;

finding in the database data acquired from a learning visual environment which are the closest to said data acquired from said least one predetermined type of visual environment; and

selecting from said database data of the prerecorded filter associated with said data of the learning visual environment which are the closest to said data acquired from said least one predetermined type of visual environment.

11. The method according to claim 1 , wherein said selecting of at least one filter is implemented by maximizing estimated performance parameters, and wherein said estimated performance parameters comprise at least one of color fidelity parameters and contrast parameters of said least one predetermined type of visual environment of the wearer.

12. The method according to claim 1 , wherein said ophthalmic device comprises a wireless communication module arranged to communicate wirelessly with at least one wireless communication device.

13. An ophthalmic device for selecting an optical filtration for a wearer, the ophthalmic device comprising means for:

obtaining wearer's preferences relative to at least one predetermined type of visual environment and taking multispectral or hyper spectral data relative to the wearer's preferences; and

selecting at least one filter:

corresponding to said wearer's preferences relative to said at least one predetermined type of visual environment, and

determined on the basis of said multispectral or hyper spectral data,

wherein said obtained wearer's preferences are obtained by at least one sensor configured to sense environment light signals; and

wherein said at least one sensor comprises a camera to acquire at least one current image comprising a multiplicity of successive lines, light signals in each band of wavelength, and in each line of said current image being measured, to generate a matrix of spatial and spectral data corresponding to same multispectral and/or hyper spectral data.