Filter for enhancing color vision

Abstract

An optical filter is disclosed that is designed to enhance color contrast even for people with normal color vision on the surface. The optical filter design relies on optimizing a set of parameters related to improved or enhanced color perception. In particular, the parameter Sigma(θ) is optimized.

Description

Cross-reference of related applications

[0001] This application claims priority to U.S. Provisional Patent Application No. 63 / 604,465, which is incorporated herein by reference in its entirety. Technical Field

[0002] This invention generally relates to optical filters for enhancing color vision. Background Technology

[0003] Optical filters are devices that act on a light source or receiver, allowing for wavelength-selective transmission. These filters can be configured to alter various aspects of color perception. Optical filters that improve or modify aspects of color vision can benefit individuals with color vision deficiencies (CVD) and those with normal color vision (NCV). Below is a list of some relevant previous research and work on color vision, color vision disorders, and visual research.

[0004] [MacLeod and Boynton, 1979] MacLeod, DIA and Boynton, RM (1979). Chromaticity diagrams of cone excitations by isoluminous stimuli. Journal of the Optical Society of America, 69(8), 1183-1186.

[0005] [Moreland et al., 2010] Moreland JD, Westland S, Zhang V, Dain SJ. (2010) Quantitative assessment of commercial filter “assistive tools” for individuals with red-green color defects. Ophthalmic Physiol Opt. Sep;30(5):685-92.

[0006] [CIE, 2004] CIE TC 8-01 (2004). Color appearance model for color management systems. Publication No. 159. Vienna: CIE Central Bureau. ISBN 3-901906-29-0.

[0007] [Winkler et al., 2015] Winkler AD, Spillmann L., Werner JS, and Webster MA, (June 29, 2015) Perception of blue and yellow and the asymmetry of “skirt” color, Current Biology, Vol. 25, No. 13, PR547-R548.

[0008] [Munsell, 1976] Munsell Colors - Glossy Collection, Munsell Color, Baltimore, Md., 1976 (https: / / sites.uef.fi / spectral / databases-software / munsell-colors-glossy-all-spectrofotometer-measured / )

[0009] [IES 2020] Illuminating Engineering Society. 2020. ANSI / IES TM-30-20 Method for Evaluating the Color Rendering of Light Sources. New York. 34 pages. Technical memorandum describing the TM-30 method. Reflectance spectrum on page 4. Figure 1 The data for the reflectance spectrum and the CIE illuminator D65 are shown in the image. These can be obtained from the file “IES TM-30-18 Advanced CalculationTool v2.01.xlsm”, which is downloaded here along with this memorandum: https: / / store.ies.org / product / tm-30-20-ies-method-for-evaluating-light-source-color-rendition / ?v=7516fd43adaa. This technical memorandum, the reflectance spectrum data, and the entire contents of the file “IESTM-30-18 Advanced CalculationTool v2.01.xlsm” are incorporated herein by reference.

[0010] [Stockman et al., 1999] Stockman A., Sharpe LT, and Fach CC (1999). Spectral sensitivity of human short-wavelength visual cones. Vision Research, 39, 2901-2927. The full text of this journal article is incorporated herein by reference.

[0011] [Stockman et al., 2000] Stockman A. and Sharp LT (2000). Deriving the spectral sensitivity of mid- and long-wavelength sensitive cones from measurements of observers with known genotypes. Vision Research, 40, 1711-1737. The full text of this journal article is incorporated herein by reference.

[0012] [Kaneko et al., 2020] Kaneko S, Kuriki I, Andersen SK. (2020). Steady-state visual evoked potentials from the early visual cortex reflect both the perception of color space and the cone antagonism mechanism. Cereb Cortex Communications. Sep 1; 1(1): tgaa059. Summary of the Invention

[0013] This application discloses a filter designed to enhance color contrast even in individuals with superficially normal color vision. The filter design will also benefit NCV (Natural Color Vision Defects) due to disease or age. The filter design relies on optimizing a set of parameters related to improving or enhancing color perception. Specifically, the parameter Sigma(θ) is optimized. Sigma(θ) is defined as:

[0014]

[0015] Where θ is the angle of the measurement axis relative to the horizontal plane, and σ F σ(θ) is the standard deviation of the chromaticity coordinates of the reflective surfaces in the color set, calculated with the filter present, and σ(θ) is the standard deviation of the chromaticity coordinates of the reflective surfaces in the color set, calculated without the filter present. The preferred color and reflectance set is the color and reflectance set used in ANSI / IES TM-30-20 [IES2020]. The entire contents of the ANSI / IES TM-30-20 standard and its associated color samples and reflectance sets are incorporated herein by reference.

[0016] In one embodiment, the optical filter has a transmission spectrum that gives a maximum Sigma(θ) value at θmax and a minimum Sigma(θ) value at θmin, wherein the maximum Sigma(θ) value is greater than 35 and θmax is between 20 and 60 degrees, and wherein the minimum Sigma(θ) value is between -10 and 10. In another embodiment, the optical filter has a transmission spectrum that gives a maximum Sigma(θ) value at θmax and a minimum Sigma(θ) value at θmin, wherein the maximum Sigma(θ) value is greater than 25, θmax is between 20 and 60 degrees, and the minimum Sigma(θ) value is between -6 and 6.

[0017] In some embodiments, the filter has chromaticity measured under a D-65 illuminator, having a chromaticity distance of less than 0.0200 from the illuminator's chromaticity in the CIE 1931 2-degree color space, a correlated color temperature greater than 4,500 K and less than 7,000 K, and visible light transmittance greater than 9% and less than 18%, preferably greater than 11% and less than 16%. In some embodiments, the filter has chromaticity measured under a D-65 illuminator, having a chromaticity distance of less than 0.0200 from the illuminator's chromaticity in the CIE 1931 2-degree color space, a correlated color temperature greater than 4,500 K and less than 7,000 K, and visible light transmittance greater than 18% and less than 40%, preferably greater than 22% and less than 29%, and even more preferably greater than 24% and less than 27%.

[0018] In some embodiments, the filter has chromaticity measured under a D-65 illuminant, which is less than 0.0200 chromaticity from the illuminant in the CIE 1931 2-degree color space, wherein for Class 3 and Class 2 sunglass lenses, the filter reduces luminance by approximately 8 to 18% VLT or 18 to 40% VLT, respectively, with a correlated color temperature between 4,500 and 7,000 K, a maximum saturation greater than 1.45 (45%) and an orientation between 20 and 40 degrees, and a minimum saturation between -1.05 and 1.05 (-5 and +5%) and an orientation approximately orthogonal to the angle of maximum saturation.

[0019] In some embodiments, the filter also has a polarizing element. In some embodiments, the minimum Sigma(θ) value of the filter is between -10 and 10, and θmin is between 80 and 120 degrees. Attached Figure Description

[0020] Figure 1 The Sigma(θ) plot of the NCV-107 example is shown.

[0021] Figure 2 The Sigma(θ) plots of embodiments NCV-101, NCV-102, and NCV-103 are shown.

[0022] Figure 3 This is the spectral transmission diagram of the HT-S50 polarizer.

[0023] Figure 4 The Sigma(θ) plots of embodiments P-200 (NCV-200) and P-204 (NCV-204) are shown.

[0024] Figure 5 Showcase SuperX ® The polarization filter has a transmission spectrum of 400 to 700 nm.

[0025] Figure 6 Showcase SuperX ® The Sigma(θ) diagram of the filter, i.e., r F Polar coordinates of (θ). Detailed Implementation

[0026] This invention relates to color contrast enhancement glasses for individuals with apparent normal color vision (NCV). The filter design will also be beneficial for NCV with acquired color vision deficiency (CVD) due to disease or age. The filter design relies on optimizing a set of parameters related to improved or enhanced color perception. Specifically, the filter controls color differences, which can be expressed as a magnitude along a specific direction in the cone excitation space (CES). Filter performance is analyzed in the McLeod-Boynton CES (McLeod & Boynton, 1979), which is modified to scale more uniformly in perception. Filters can also be used in CMF-based color spaces (e.g., CIE 1931, CIE 1965, etc.). Filters can be analyzed in the LCH color space. This allows filter properties (such as VLT, ΔE, CCT, chroma, primary hue, and chroma) to be combined with performance values ​​from CES analysis to fully characterize the filter.

[0027] Analysis can be performed using any reflectance color set representing the full color space. Candidate sets will be discussed. For the purposes of this invention, we use the reflectance set (TM-30 reflectance set) used in the ANSI / IES TM-30-20 standard. [IES2020] Performance is measured by calculating the standard deviation of said set and examining changes in the L and S values ​​in the CES. For NCV, it is desirable to increase color contrast along the L direction in the CES, and it is desirable for color contrast along the S direction to remain almost unchanged. This is equivalent to an increase in the standard deviation of the set for L and a smaller change in the standard deviation of the set for S. In addition, scalars L and S can be transformed into polar coordinate equivalents of vectors r and angles, and performance is evaluated as a function of angles in the CES. Filters describing an ellipse with the largest standard deviation approximately along the lime green-magenta direction (corresponding to a line bisecting 45° to 225° through the neutral point) are found to have the best performance. The optimal performance region corresponds to an ellipse with a major axis angle of approximately 20 to 60°, bisected by the neutral point, up to 200° to 240°. Relative to a circle, the increase in r along this line should be greater than 25% (a circular profile implies that the filter's performance remains unchanged, just like a perfect neutral density filter). The corresponding minor axis should be rotated approximately 90° relative to the major axis and have a corresponding r close to 1.

[0028] The transformed set can be evaluated as a frustum angle or hue angle in either the CES or CIE type color space, respectively. CES results can only be transformed to the CIE XYZ color space for NCVs where the CMF is explicitly defined. Transforming to CIE XYZ allows filter hues (such as hue, saturation, and lightness as seen in NCV) to be evaluated as chromaticity values ​​(e.g., [x,y]; [u',v']). The design algorithm sets chromaticity limits to establish a roughly neutral color (with a small ΔE relative to a set of reference illuminators) and maintains a correlated color temperature (CCT) value close to the design illuminator (e.g., D-65 daylight) and the set of reference illuminators (e.g., the D series). These describe “secondary” design criteria and are as important as the primary design goal of increasing overthreshold color saturation along the lime-green-magenta direction while keeping color saturation almost constant along the cyan-orange direction. The underlying principle behind imposing secondary design criteria is that color perception has evolved along an orange-cyan axis tuned for sky-earth, which plays a role in determining scene illuminators by evaluating reflective surfaces. Maintaining a neutral filter color and CCT close to the design illuminator keeps this relationship intact (without the blue skirt effect). Furthermore, higher-order color vision mechanisms are tuned to these perceived hue directions and, in the case of orange-cyan, rely on this information to determine the edge positions and object properties of indirect (blue sky) and direct (yellow sunlight) illumination. Experimental evaluations of filter designs have revealed that the filter chromaticity should remain close to the illuminator chromaticity, which also maintains the filter CCT close to the illuminator CCT. Therefore, filter designs adhering to these guidelines should have small ΔE and small ΔCCT relative to D-series illuminators (D50, D55, D60, D65, D70, D75, D80). Maintaining a small ΔE (below 0.0200) for each illuminator automatically keeps the ΔCCT small.

[0029] Detailed description

[0030] There are various methods for evaluating filter performance, which involve calculating the color space coordinates of a set of reflective surfaces with and without filters. Typically, the goal of a color-enhancing filter is to increase the saturation of a color set or subset. In an isoluminance chromaticity space, the saturation of a color is related to its distance from the white point. Therefore, the effect of a filter on color saturation can be evaluated by modeling how the filter alters the distance between the reflective surfaces of the color set and the white point.

[0031] In the Sigma method, the standard deviation of the chromaticity coordinates of the reflective surface in a color set is calculated in both cases with and without filters. The standard deviation serves as a convenient method for quantifying the average distance from the white point and is a measure of the "expansion" of the set. The color set must be uniformly distributed across the color space such that the average chromaticity coordinates of the set approximate the coordinates of the white point. The standard deviation is calculated separately for each of the two orthogonal axes of the chromaticity space to measure the expansion in each dimension. In other words, the standard deviation is calculated separately for the horizontal and vertical coordinate sets. We label these two values ​​as Sigma-L and Sigma-S, reflecting the horizontal coordinate (L / (L+M)). 1 / 3 and the ordinate (S / (L+M)) 1 / 3 The percentage change in the horizontal and vertical standard deviations caused by a filter is a measure of the filter's performance along these axes. The term "Sigma" is used here to refer to this percentage change in the standard deviation along a specified axis caused by the filter. Because Sigma is a percentage change, it can take any value, positive or negative, where a positive value indicates an increase (expansion) in the average saturation of the color set along the specified axis, and a negative value indicates a decrease (contraction) in the average saturation.

[0032] Sigma(θ)

[0033] Sigma can also be calculated along axes other than horizontal and vertical. This is done by first calculating the chromaticity coordinates with and without a filter, then rotating the axis by an angle θ relative to the horizontal by multiplying each pair of chromaticity coordinates by a rotation matrix. The standard deviation of the new set of horizontal coordinates is then calculated. This process is repeated for values ​​of θ ∈ [0°, 180°) to obtain the function Sigma(θ). The value of Sigma(θ) represents the performance (expansion / contraction) of the filter in polar coordinate CES. Since Sigma(θ) measures expansion / contraction along a given axis in both the positive and negative directions, it repeats after 180° and is symmetric about the origin. Note also that the Cartesian values ​​of the horizontal (Sigma-L) and vertical Sigma (Sigma-S) are equal to Sigma(0°) and Sigma(90°), respectively.

[0034] Each value of Sigma(θ) has a magnitude r, which is a performance measure as a function of angle. The radius of the curve at a given angle is equal to 1 + Sigma(θ) / 100. A radius greater than 1 indicates a positive sigma value at that angle (expansion along the axis), a radius less than 1 indicates a negative sigma value (contraction), and a radius equal to 1 indicates no change. Therefore, the unit circle represents the case without a filter. Filter curves can be plotted relative to the unit circle to visualize the filter's effect. Filter curves typically tend to be elliptical, with the major axis aligned along the direction with the maximum sigma and the minor axis aligned along the direction with the minimum (or most negative) sigma.

[0035] Filters designed to enhance the contrast and saturation of certain colors rather than others are a well-known technique. This invention designs filters from multiple narrowband and broadband absorbers (e.g., polarizing films). The filter designs are then analyzed in several color spaces, primarily the modified McLeod-Boynton cone excitation space (CES) and the CIE color space, 2 degrees 1931 or 10 degrees 1965. The design method is known as Sigma. Sigma examines a set of reflective surfaces (reflectivity set) and evaluates the performance of filter designs for color-normal (NCV) individuals, wherein the designed filters are placed in an optical path originating from a standard illuminator (e.g., CIE D-65 standard daylight). Several sets of available reflective surfaces may be 100 reflective surfaces from TM-30. [IES 2020] The appeal of TM-30 lies in its widespread downloadability and embedding into the widely available and free analysis tool IES TM-30-18 Basic Calculation Tool v2.01. [IES 2020] Our primary method for analyzing filter designs is to observe the standard deviation of the reflectance set. Similar to CVD, exemplary filter designs for NCV will keep Sigma-S relatively constant and significantly increase Sigma-L. An optimal angular range, Sigma(θ) ∈ {20 to 45°}, is also found, corresponding to ideal color enhancement for green and red. Therefore, a function of the design tool is to increase Sigma(θ) ∈ {20 to 45°}. .

[0036] An optimal filter design for improving color perception in NCVs can improve the perceived color contrast of red and green in the reference set while keeping blue and yellow unchanged. For Sigma purposes, the reference set is displayed in the cone excitation space (CES), specifically the modified McLeod-Boynton CES, where the x-axis and y-axis represent the red-green and blue-yellow primary color axes, respectively, denoted by L and S. Each reflective surface can be defined as a point in the CES by taking the product of its spectrum, the reference light source, and the linear energy cone sensitivity set, resulting in three products L, M, and S. These three values ​​are used to construct the distribution of {L, S} values ​​for the reference set, where the x-axis is L / (L+M) and the y-axis is S / (L+M). This can be further modified by taking the cube root: L = [L / (L+M)]. 1 / 3 And S = [S / (L+M)] 1 / 3 This final step makes the color space more perceptually uniformly scaled. One benefit of CES is that it represents the second, post-receptor stage of color vision processing, where cortical mechanisms evaluate input from the LGN—closer to perception than signal. For normal color vision (NCV), the set of photopigment sensitivity functions {L,M,S} is used. A good source for {L,M,S} is the Colour & Vision Research Laboratory at cvrl.org.

[0037] For NCV, filter designs that result in greater separation between the M and L cones through wavelength-selective narrowband filtering will be translated into Sigma-L added in CES. Some M- or L-stimulus-dominant colors that might otherwise be undetectable due to physical size or distance limiting the viewing angle, being embedded in chromatic or luminance noise, or being obscured by broadband noise (fog or haze) become more easily perceived. For effectiveness, the increase in color saturation must be appropriately oriented in CES. The lime-green-magenta and orange-cyan directions represented in CES are associated with higher-order visual processes originating in the primary visual cortex V1. Optimizing color contrast and perception along these universal color directions should improve the performance of tests designed to measure color contrast, color naming, and color scaling.

[0038] Other filter evaluation methods exist, and some are similar to this invention. Two of the most relevant methods are ANSI / IES TM-30 [IES 2020] and the method proposed by Morland [Moorland et al., 2010]. ANSI / IES TM-30 (TM-30) is a method published by the Illuminating Engineering Society and used by the American National Standards Institute for evaluating the color rendering of illuminants. This method can be reused to evaluate filter designs by multiplying the illuminant spectrum by the filter spectrum and using the result as the test illuminant in the TM-30 method.

[0039] The TM-30 method is similar to Sigma in that both model the effect of the test spectrum relative to a reference on a set of reflectance spectra. TM-30 calculates isoluminance chromaticity coordinates (in CIE CAM02-UCS [CIE, 2004]) of a set of 100 reflectance spectra under both the test illuminator and the reference illuminator (a CIE D-series illuminator with the same color temperature as the test illuminator). Colors are grouped into one of 16 color bins based on their hue angle under the reference illuminator. For both the reference and test illuminators, the chromaticity coordinates of each color in the color bin are averaged. Variations in this average for each color bin are used to quantify the effect of the test illuminator on the colors in that bin, and various metrics are calculated based on these variations to convey information about the color rendering properties of the test illuminator.

[0040] One way the TM-30 displays this information is through a curve called a "color vector diagram." This is a two-dimensional curve defined by 16 points (one point per color group), where each point is offset away from the unit circle according to its relative change from the average coordinates of the color group. It is similar to the Sigma filter curve, where the invariant condition is the unit circle, and the filter tends to create an ellipse. In fact, the color vector diagram was inspired by the Sigma filter curve because it is an intuitive and visual way to demonstrate the effect of the filter (or illuminator) on different colors.

[0041] However, there are some key differences between Sigma and TM-30. One difference is that Sigma compares the filtered illuminant to the same unfiltered illuminant, while TM-30 (suitable for evaluating filters) compares the filtered illuminant to different illuminants of the same color temperature. In some cases, this can result in the TM-30 using a significantly different reference illuminant than the Sigma using.

[0042] Another difference between TM-30 and Sigma is that TM-30 evaluates different color groups separately. Sigma, on the other hand, evaluates how the entire set changes. This means that, for example, if TM-30 shows increased saturation in color group 1, it only indicates that the colors in color group 1 have increased chromaticity, not the situation for any other colors. In contrast, if Sigma(θ) shows an increase at the same angle, it means that the saturation of every color in the set increases on average along that axis.

[0043] The Morland method, referred to in this paper as the Morland-Dane method (MDM) [Moland et al., 2010], is more similar to the Cartesian embodiment of Sigma. MDM is used to evaluate filters marketed to assist CVD. Therefore, MDM uses LL'S, M'MS, and LMS cone spectra to evaluate filters for CVD types and presents performance in a modified McLeod-Boynton CES. Variations in the standard deviation of a large set of reflectivity surfaces are the primary metric. Filters showing little increase in the standard deviation of this set are considered to have poor performance. MDM does not use transformation matrices to evaluate filter designs in polar coordinate CES, therefore it does not provide information about the performance of individual color axes L and S or their reorientation to the maximum and minimum axis values ​​of the rotation ellipse.

[0044] Contrast Enhancement Filter Design for NCV

[0045] Design for CVD

[0046] Sigma can be used to design filters for both NCV and CVD. This design tool has allowed the inventors to design high-performance color contrast enhancement (CCE) filters for aberrant trichromatic CVD. Furthermore, {L,S} can be calculated for both NCV and CVD with and without filters. Comparisons can then be made relative to NCV, providing a performance quality factor. Filter performance analysis is as follows. The standard deviation of a reference set was calculated for NCV and six CVD cases representing mild, moderate, and severe deutan and protan CVD. Because CVD causes CES to collapse along the x-axis (red-green) rather than the y-axis (blue-yellow), the magnitude of the standard deviation of L decreases, while the standard deviation of S remains relatively unchanged (Table I). The greater the degree of CVD, the more pronounced the collapse in the red-green direction, and therefore the smaller the standard deviation of L. Introducing filters into the calculations allows for an evaluation of their performance, as mentioned, this can be done relative to the standard deviation of the NCV set and given as a percentage. It may be convenient to express the performance improvement as a ratio to the NCV without a filter, or as an ellipticity relative to a unit value of 1.

[0047] Design for NCV

[0048] There are some significant differences in the design for NCV. The first significant difference is the preferred directional offset in the CES away from the fundamental axis. For NCV, the design goal is to maximize Sigma-L and minimize Sigma-S along the diagonal axis between the fundamental directions LM and S in the CES. These axes correspond to lines bisecting angles from 45° to 225° and from 135° to 315° (-45°). The color response is tuned to these non-fundamental color directions, aligned with lime-green-magenta and orange-cyan, respectively. This directional tuning has been clearly demonstrated in the study by Kane et al. using a scanning VEP [Kane et al., 2020], with lobes having larger signal potentials corresponding to hue tuning at approximately 30° and 60°. To best analyze the filter design for NCV, Sigma is calculated as a vector sum of scalars L and S by converting the Cartesian components to polar components. Along the fundamental direction θ = 0°, Sigma(0) = L, and along the fundamental direction θ = 90°, Sigma(0) = S. The magnitude is the vector sum r.

[0049] Sigma varies with angle θ (relative to the white point in CES). To calculate the vector product of L and S, we can use a rotation matrix to convert the Cartesian set {L, S} to polar coordinates (r, θ).

[0050] It is important to clarify that the analysis is performed from multiple angles, and the results are combined. The best approach is to apply a rotation matrix in 1-degree increments from 0° to 180°. The goal is to enhance color contrast along the lime-green-magenta direction while maintaining relative stability along the orange-cyan direction. Preserving the blue-yellow or orange-cyan color relationships can affect NCV. For NCV, analyzing the colors of objects in the scene (especially colored objects along the blue-yellow axis) provides a theoretical basis for minimizing Sigma(θ) between angles of 60° to 150° and 240° to 330°. Uneven variations in the blue-yellow hues of scene objects can distort perception of the lighting volume. This can lead to confusion about what constitutes shadows versus topological features, and the relative spatial positions of these objects. [See, for example, Winkler et al., 2015]

[0051] The second significant difference between designing filters for CVD and NCV is that Sigma-L and Sigma-S are optimized for NCV rather than for CVD with weak green and red. Extensive parameter analysis has shown inventors how to manipulate the design spectrum to maintain color neutrality, maintain color temperature, and have the correct range of light transmittance, while having a large Sigma-L, a small Sigma-S, and an optimized rotation angle for Sigma(θ).

[0052] Sigma can be embedded into filter design procedures to allow for the measurement and visualization of performance during filter design. The design can be a summary of narrowband and broadband dyes, UV absorbers, polarizers, antireflective coatings, flash mirror coatings, and interference coatings. In its simplest embodiment, the filter design is constructed from the sum of the spectral extinction coefficients of i dyes, which are then weighted by concentration (c... i And it is defined for a given filter thickness (x). This is shown below.

[0053]

[0054]

[0055] For a given filter thickness x, each "i" dye has an extinction coefficient. and concentration c i Analysis can be performed in wavelength ranges of 400 to 700 nm, 380 to 730 nm, or 380 to 780 nm, typically in 1 nm steps. The optical density OD at each wavelength... λ,tot This can be expressed as the transmittance τ per wavelength. λ,tot A graphical representation can show filter designs as (λ, OD or) (λ, τ) wavelengths ranging from 400 to 700 nm.

[0056] To represent the effect of the filter on NCV, we primarily use a color space based on the LMS cone sensitivity function, rather than the more common CIE XYZ color matching function. The McLeod-Bointon CES is a representation of the LMS excitation for NCV. The x-axis represents the cone excitation of the [LM] chromaticity channel as L / (L+M). Along the y-axis, the cone excitation is represented as [S-(L+M)] as S / (L+M). The molecule is luminance. A similar analysis can be performed in the DKL CES. Normalization is used to give a white reference point, which can be an isoenergy white E, daylight D-65, or some other white reference point. We modify this CES by taking the cube root of the axis to make the space perceptually more uniform. The reflectance set {R} can also be the average value {R} of the set. mean Centered on.

[0057] To utilize this CES, we selected a set of reflective surfaces representing the real world, including both natural and man-made ones. A color set (referred to in this paper as the Pantone set) consists of 246 reflectance spectra; chlorophyll, 18 from the Xrite color checker, and Pantone... ® 220 color charts from the extended color gamut book and Pantone ®The Neon color chart contains seven more saturated colors. Another color set, called TM-30, is based on 100 reflective surfaces and is supported by IES. [IES 2020] A third set can be a set of Gaussian reflective surfaces generated by formulas, which has the advantage of equal hue angle steps and chromaticity steps. This set can be made very large (>900 reflective surfaces) or very small (16 reflective surfaces). A fourth set that can be used is 1,600 reflective surfaces from the Munsell color chart [Munsell, 1976]. Regardless of which set is chosen, Sigma produces very similar results for filter design. We will use the TM-30 set in this analysis because it is commonly used in other color analysis tools, such as IES TM-30-20, which will be discussed in detail in this paper.

[0058] To improve color perception in NCV, we can observe the effect of filter design on the Sigma value. The color experience in NCV can be altered by making certain colors appear more saturated and colors selected from opposite color categories appear more distinct (greater color contrast). A successful filter design will increase [L / (L+M)] as measured along a specific angle in polar coordinates CES using the TM-30 reflectance set. 1 / 3 The standard deviation value, with the common goal of making [S / (L+M)] equal to... 1 / 3 Minimize the variation in the standard deviation value.

[0059] To reiterate, we characterize the directional spread of data points in the CES by taking the standard deviation of the reflectance set of the NCV without a filter and comparing it with the NCV value with a filter. We denote the standard deviation Sigma of these points in the CES as (σ), where σ L The reflectance set is represented by L = [L / (L+M)]. 1 / 3 The standard deviation of the value and σ S The reflectance set is represented by S = [S / (L+M)]. 1 / 3 The standard deviation of the value.

[0060] There is a relationship between the Sigma(θ) results and the results of the IES TM-30-18 Basic Calculation Tool v2.01 (IES TM-30). [IES 2020] Both models use the TM-30 reflectance set. Sigma(θ) represents a mapping of values ​​in polar coordinates CES, where the values ​​are offset due to the designed filter. In the IES TM-30 analysis, the polar coordinates CMF space is used to map the variation in chromaticity values ​​caused by the designed filter. IES TM-30 organizes the data in 16 hue groups at an angle of 22.5°, and the angles representing hues are rotated inversely to the angles in CES. The last point needs to be considered from 360°. 0The maximum and minimum Sigma(θ) values ​​were subtracted to correlate with the IES TM-30 angle. Furthermore, the magnitude of change in r did not correlate with the change in chromaticity in any obvious way.

[0061] For the purposes of this invention, we will specifically use the Sigma(θ) results generated using the TM-30 reflectivity set.

[0062] If we consider the percentage improvement in Sigma to be relative to the unassisted NCV, and use uppercase sigma to define the improvement, then our design should make Larger and positive Approaching zero. Specifically, we expect filter designs for NCV to have the following Sigma values: Class 3 sunglass lenses: >30%; Category 2 sunglasses lenses: >15%, and For both types of sunglass lenses, the limit is + / - 10%. For NCV, the improvement is based on the NCV without a filter. and The percentage change is defined.

[0063] Keep The necessity of limiting it to near zero has been experimentally proven and can be explained in color theory. Filter designs outside the -10 to +10 range result in color distortion. Filter designs can simultaneously achieve low... And a large ΔE, meaning almost no blue-yellow or cyan-orange color distortion, but a highly tinted filter. This is clearly undesirable and demonstrates the need to control non-CES values ​​when designing exemplary filters.

[0064] Sunglasses designed for normal color vision

[0065] To design high-efficiency color contrast enhancement (CCE) glasses for NCV, the goal is to provide a maximum Sigma(θ) (>30), a minimum Sigma(θ) (<6), where the angle of the maximum Sigma(θ) is between 20° and 60° and the angle of the minimum Sigma(θ) is approximately orthogonal to the angle of the maximum, low ΔE (<0.0100), VLT between 8 and 18% (Class 3) or between 18 and 40% (Class 2), and CCT between 5,000 and 9,000 K.

[0066] The design was carried out in a revised version of the McLeod-Boynton CES. The cone signal was converted into the difference (LM) and (S-(L+M)) representing the retinal layer values ​​of the chromaticity channels. Cortical processing made the representation more aligned with the lime-green-magenta and orange-cyan directions in the color space.

[0067] To better understand the relationship between the spectral response of cone cells (the spectral sensitivity curves of L, M, and S photosensitive pigments) and their CVD counterparts L' (weak green) and M' (weak red), this paper analyzes the data based on color channel values. The red-green channel carries the difference between the L and M cone signals, while the blue-yellow channel carries the difference between the S signal and the sum of the L and M cone signals. This information can be used to determine the optimal wavelength for absorbing signals to enhance color vision.

[0068] One design approach is fundamental. For the three photosensitive pigments, we need at least two absorption bands to alter the quantum trapping of the photosensitive pigment. The first step is to differentiate the wavelength with respect to S-(L+M) and find the wavelength with a slope of zero. This is 480 nm for NCV. Next, we take the second derivative with respect to the wavelength of the second channel value (LM) and find the inflection point, which is the maximum value. This is 582 / 3 nm for NCV. A design based on this analysis will have two absorption bands. The absorption band at 480 nm is used to maintain a minimum change in the Sigma(θ) value, and the absorption band at 582 / 3 nm is used to maximize the signal difference between the L cone and M cone signals for a given stimulus.

[0069] Condition 1: S-(L+M) is the minimum value: [S-(L+M)] / λ=0

[0070] Condition 2: LM is an inflection point: maximum value:

[0071] Exemplary Examples

[0072] Starting with the conditions defined above, the filter is designed using the summation method of extinction coefficients described above, and analyzed using the Sigma method described above. In the exemplary embodiment, the filter is designed to have a high maximum Sigma(θ) value, a minimum Sigma(θ) value close to zero, a maximum Sigma(θ) rotation angle much higher than the horizontal axis, a CCT that is neither too low (brownish-white) nor too high (bluish-white), and a chromaticity close to the blackbody locus, thereby maintaining a neutral tinted lens.

[0073] The design is based on a weighted selection of twelve dyes. Tables Ia and Ib provide a set of selection examples.

[0074] Table Ia.

[0075]

[0076] Table Ia presents the Sigma analysis for normal color vision. Design of color contrast enhancement filters NCV-107 to NCV-113: Sigma values ​​are calculated for the TM-30 reflectance set. Sunglasses lens categories and calculated values ​​for VLT, ΔE-illuminator (D65), average ΔE-illuminator (D series), and CCT are shown. Sigma(θ) values ​​are calculated using the D-65 illuminator and the TM-30 reflectance set. Sigma(0) = Sigma-1, Sigma(90) = Sigma-S, and the angles of maximum and minimum Sigma(θ) are determined in 1-degree steps from 0° to 180°. VLT is visible light transmittance. ΔE is measured in the 1931 2-degree CIE chromaticity diagram and is the vector distance from the chromaticity of the filter design to the chromaticity of the illuminator. CCT is correlated color temperature, measured in Kelvin.

[0077] Table Ib.

[0078]

[0079] Table Ib presents the Sigma analysis for normal color vision. Design of color contrast enhancement filters NCV-114 to NCV-119: Sigma values ​​are calculated for the TM-30 reflectance set. Sunglasses lens categories and calculated values ​​for VLT, ΔE-illuminator (D65), average ΔE-illuminator (D series), and CCT are shown. Sigma values ​​are calculated using the D-65 illuminator and the TM-30 reflectance set. Sigma(0) = Sigma-1, Sigma(90) = Sigma-S, and the angles of maximum and minimum Sigma are determined in 1-degree steps from 0° to 180°. VLT is visible light transmittance. ΔE is measured in the 1931 2-degree CIE chromaticity diagram and is the vector distance from the chromaticity of the filter design to the chromaticity of the illuminator. CCT is correlated color temperature, measured in Kelvin.

[0080] Tables Ia and Ib showcase designs with excellent performance values. In all examples, the maximum Sigma(θ) has a value greater than approximately 35, the minimum Sigma(θ) has a value between 0 and -4, and the maximum angle is between 30° and 40°. Filters based on these designs with exemplary Sigma values ​​and this tuned elliptic orientation should enhance colors roughly along the lime-green-magenta color axis, while showing almost no change in color along the cyan-orange color axis.

[0081] All VLT designs, within the appropriate Class 2 sunglass lens range, have a ΔE below 0.200 (except for NCV-109 and NCV-110) and a CCT of 4,500 to 7,000K. Examples NCV-209 and NCV-110 are included to demonstrate exemplary performance beyond ΔE-illuminator (D65) and ΔE-II (D series). These two examples fail to maintain lens color neutrality during changes in daylight phase from warm (D50) to cool (D80).

[0082] The Sigma(θ) plots selected for the NCV-107 and NCV-108 filters in Table Ia are shown in [the original text]. Figure 1 The “Sigma(θ) plot” is a polar coordinate graph of the r-value.

[0083] It is possible to create designs with extremely high Sigma-L values, but at the cost of other desired properties. Table Ic explores this in a finite number of examples.

[0084] Table Ic.

[0085]

[0086] Table Ic presents the Sigma analysis for normal color vision. Design of color contrast enhancement filters NCV-101 to NCV-105: Sigma(θ) values ​​are calculated for the TM-30 reflectance set. Sunglasses lens categories and calculated values ​​for VLT, ΔE-illuminator (D65), average ΔE-illuminator (D series), and CCT are shown. Sigma(θ) values ​​are calculated using the D-65 illuminator and the TM-30 reflectance set. Sigma(0) = Sigma-1, Sigma(90) = Sigma-S, and the angles of maximum and minimum Sigma(θ) are determined in 1-degree steps from 0° to 180°. VLT is visible light transmittance. ΔE is measured in the 1931 2-degree CIE chromaticity diagram and is the vector distance from the chromaticity of the filter design to the chromaticity of the illuminator. CCT is the correlated color temperature, measured in Kelvin.

[0087] Table Ic provides examples of maximum Sigma(θ) values ​​greater than 35, greater than 45, and in one case 55, while minimum Sigma(θ) remains low. NCV-101 has excessively high ΔE-illuminator and average ΔE-il (D series), excessively high CCT, and excessively low maximum Sigma angle. NCV-102 has excessively high ΔE-illuminator and average ΔE-il (D series), excessively high CCT, and excessively low maximum Sigma angle. NCV-103 has slightly above-acceptable ΔE-il and average ΔE-il (D series), but otherwise exhibits high performance. NCV-104 is an exemplary high-Sigma-L Class 2 sunglass filter design. NCV-105 has excessively high ΔE-illuminator and average ΔE-il (D series), but otherwise exhibits high performance. NCV-106 is an exemplary high-Sigma-L Class 3 sunglass filter design.

[0088] The Sigma(θ) diagrams for the filter designs NCV-101, NCV-102, and NCV-103 in Table Ic are shown in... Figure 2 It is displayed in the middle.

[0089] Three types of polarization versions can also be created for NCV. Examples are given in Table Id, and the polarizers used in this analysis are... Figure 3 The image is displayed as a spectrum.

[0090] Table Id.

[0091]

[0092] Table Id presents the Sigma analysis of the polarizing filter design for normal color vision. The polarizing filter is HT-S50 (see...). Figure 2 ). Sigma values ​​are calculated for the TM-30 reflectivity set. The sunglass lens categories and calculated values ​​for VLT, ΔE-illuminator (D65), average ΔE-illuminator (D series), and CCT are shown. Sigma values ​​are calculated using the D-65 illuminator and the TM-30 reflectivity set. Sigma(0) = Sigma-1, Sigma(90) = Sigma-S, and the angles of maximum and minimum Sigma are determined in 1-degree increments from 0° to 180°. VLT is visible light transmittance. ΔE is measured in the 1931 2-degree CIE chromaticity diagram and is the vector distance from the chromaticity of the filter design to the chromaticity of the illuminator. CCT is correlated color temperature, measured in Kelvin.

[0093] Table Id provides examples of polarizing filter designs. NCV||P||-107 is an exemplary Class 3 polarizing sunglass lens with high maximum and maximum Sigma. NCV||P||-113 is a Class 3 polarizing sunglass lens with excessively high ΔE-illuminator and average ΔE-Ill (D series), while exhibiting high performance in other properties. NCV||P||-200 is an exemplary Class 3 polarizing sunglass lens with high maximum and maximum Sigma. NCV||P||-201 is an exemplary Class 3 polarizing sunglass lens with high maximum and maximum Sigma. NCV||P||-202 is an exemplary Class 3 polarizing sunglass lens with high maximum and maximum Sigma. NCV||P||-203 is an exemplary Class 3 polarizing sunglass lens with high maximum and maximum Sigma. NCV||P||-204 is a Class 3 polarizing sunglass lens with excessively high ΔE-illuminator and average ΔE-Ill (D series), while exhibiting high performance in other properties. NCV||P||-205 is an exemplary Class 3 polarized sunglass lens with high maximum Sigma and maximum Sigma.

[0094] The Sigma(θ) plot of the filter design NCV-107 in Table Id is shown in... Figure 1 The Sigma(θ) plots for filter designs P-200 (NCV-200) and P-204 (NCV-204) in Table Id are shown in [the table]. Figure 4 It is displayed in the middle.

[0095] In the case of NCV (Non-Concentrated Color Vibration), maintaining the blue-yellow hue of objects is important as it helps maintain the consistency of the illuminated object. In our filter design, there is a high... ,Low And many instances of high ΔE, but no high ΔE. ,high Examples of low ΔE. If the filter has neutral colors, then blue-yellow distortion is minimal. This is a strong argument for maintaining color neutrality in eyeglasses (especially those intended for users with low vision). (See Table Id and...) Figure 4 Examples of this effect are illustrated in the designs P-200 and P-204. Figure 4 In the table, feature “1005” indicates the position where the minimum Sigma value of P-204 (NCV-204) increases relative to P-200 (NCV-200), and this has an effect on the ΔE-illuminator shown in Table 1-d: the value increases by more than double, resulting in a reduction in the neutral color of the filter and more distortion along the blue-yellow direction.

[0096] Calculate SuperX ® Sigma(θ) of the filter

[0097] The process of calculating Sigma(θ) is described in detail below. SuperX ® Filters are used for instance calculations. Figure 5 SuperX ® It is a sunglass lens filter based on polycarbonate, featuring a green anti-reflective front coating and a neutral anti-reflective back coating. Super-X ® It is a Class 3 sunglass lens, polarized, and has excellent performance.

[0098] set up It is a 100 x 301 matrix, where each row contains 100 reflectance spectra used in the ANSI / IES TM-30-20 standard, with a step size of 1 nm and a range of [400, 700]. [IES 2020] Let... , and It is a 301 x 1 matrix of the spectral responses of L, M, and S cone cells, with a step size of 1 nm and a range of [400, 700]. [Stockman et al., 1999][Stockman et al., 2000] Let... It is a 301 × 1 multiplication matrix of the CIE D65 illuminator, with a step size of 1 nm and a range of [400, 700]. [IES2020] Let... It is a 301 × 1 matrix of the transmission spectrum of the filter under consideration, with a step size of 1 nm and a range of [400, 700].

[0099] The LMS coordinates of each color in the color set are calculated as follows, both with and without filters:

[0100]

[0101]

[0102] Equation 1

[0103] The symbol ⊙ represents element-wise multiplication. Indicates matrix multiplication. Subscript F This indicates that the corresponding value should be calculated when a filter is present. , , , , , It is a 100 x 1 matrix containing the L, M, and S coordinates of each of the 100 colors in the color set.

[0104] Table II.

[0105]

[0106] Table II shows 0.69284 Instance calculation.

[0107] Table III.

[0108]

[0109]

[0110] Table III shows SuperX ® 0.69284 for the filter Instance calculation.

[0111] Table IV.

[0112]

[0113] Table IV shows the reflectance spectrum from the TM-30 color set. A fragment.

[0114] Table V.

[0115]

[0116] Table V shows SuperX ® Filters , , , , , Some of the values ​​obtained.

[0117] set up , , and It is a 100 x 1 matrix representing the coordinates of each color in the color set in the frustum excitation space, with and without filters. , , and The i-th element in the matrix is ​​calculated as follows:

[0118]

[0119]

[0120]

[0121]

[0122] Equation 2

[0123] Where Li M i S i L Fi M Fi S Fi They are , , , , , The i-th element in.

[0124] Table VI.

[0125]

[0126]

[0127] Table VI showcases the SuperX® filter. , , and Some of the values ​​obtained.

[0128] set up and It is the set of spatial coordinates excited by the cone of view along an axis at an angle θ to the horizontal. This is equivalent to rotating the coordinate axes by an angle -θ. It is calculated as follows:

[0129]

[0130]

[0131] Equation 3

[0132] Let σ(θ) and σ F (θ) is and The standard deviation is calculated as follows:

[0133]

[0134]

[0135] Equation 4

[0136] Where μ(θ) and μ F (θ) are respectively and The average value is N, where N is the vector length of 100.

[0137] Let Sigma(θ) be σ F The percentage change of (θ) relative to σ(θ):

[0138]

[0139] Equation 5

[0140] These calculations are repeated for angles between [0°, 180°). Because of 180° rotational symmetry, the values ​​for angles between [180°, 360°) are the same and do not need to be calculated. Sigma(θ) can be represented in a polar graph as the deviation from the unit circle. In this graph, the unit circle represents the color set without a filter, i.e., without change. The effect of the filter is represented by polar curves:

[0141]

[0142] Equation 6

[0143] This function is defined for angles between [0°, 360°) to create a closed curve, where the value for the angle [180°, 360°) is equal to the value for [0°, 180°). A graph of the function helps visualize the effect of the filter, particularly the maximum and minimum values ​​and the angles at which they occur.

[0144] The following table shows SuperX ® Example calculation of this process for the filter.

[0145] Table VII-a.

[0146]

[0147] Table VII-a contains information for SuperX. ® Filter at θ=45° Sample calculation.

[0148] Table VII-b.

[0149]

[0150] Table VII-b contains information for SuperX. ® Filter at θ=45° Sample calculation.

[0151] Table VIII.

[0152]

[0153] Table VIII shows the information regarding SuperX. ® Some obtained values ​​of Sigma(θ) for the filter at different θ values. σ(θ) and σ F (θ) is calculated from equation 5. and The standard deviation.

[0154] Table IX.

[0155]

[0156]

[0157] Table IX shows the benefits for SuperX. ® Filter r at different θ values F Some obtained values ​​for (θ). This data is in Figure 6 Draw in the middle.

[0158] Table X.

[0159]

[0160] Table X shows SuperX ® The relevant Sigma(θ) values ​​for the filter. Sigma(0) is the value of Sigma(θ) at angle θ = 0°. Sigma(90) is the value of Sigma(θ) at angle θ = 90°. Maximum Sigma(θ) is the maximum value of Sigma(θ), and θmax is the angle at which the maximum value occurs, in degrees. Minimum Sigma(θ) is the minimum value of Sigma(θ), and θmin is the angle at which the minimum value occurs, in degrees.

[0161] Lens brightness and color rendition are also important qualities of a well-designed filter. These can be quantified using the CIE 1931 color space and a 2-degree standard observer. The xyY values ​​of the filter should be calculated using the CIE D65 illuminant. These can then be expressed as quantities VLT and ΔE. I VLT equals the CIE Y value expressed as a percentage. ΔE I The Euclidean distance from the filter color to the illuminator color in the xy chromaticity space:

[0162]

[0163] Equation 7

[0164] Where x and y are the xy chromaticity coordinates of the filter with CIE D65 illuminant, and x I and y I These are the chromaticity coordinates of the CIE D65 illuminant without a filter.

[0165] Table XI.

[0166]

[0167]

[0168] Table XI contains SuperX ® Other relevant values ​​for the filter. The properties of the polarizing Super-X filter lie in its approximately 2.0 mm lens thickness. For sunglass lenses, Class 3 has a transmittance of 8% to 18%, with visible light transmittance (VLT) within Class 3, and ΔE... I (D65) is the Cartesian distance from the illuminator (D65) and the filter plus illuminator in the CIE 1931 2-degree color space. The average ΔE-Ill (D series) is the average Cartesian distance of the D-illuminator group (D50, D55, D60, D65, D70, D75, D80) in the CIE 1931 2-degree color space. CCT is the correlated color temperature, and the unit is Kelvin.

[0169] Super-X filters are polarized sunglasses lenses. The lens categories and calculated values ​​for VLT, ΔE-illuminator (D65), average ΔE-illuminator (D series), and CCT are shown. Sigma(θ) values ​​are calculated using the D-65 illuminator and the TM-30 reflectance set. Sigma(0) = Sigma - L, Sigma(90) = Sigma - S, and the angles of maximum and minimum Sigma(θ) are determined in 1-degree steps from 0° to 180°. VLT is the visible light transmittance. ΔE is measured in the 1931 2-degree CIE chromaticity diagram and is the vector distance from the chromaticity of the filter design to the chromaticity of the illuminator. CCT is the correlated color temperature, measured in Kelvin.

Claims

1. An optical filter having a transmission spectrum that gives a maximum Sigma(θ) at θmax and a minimum Sigma(θ) at θmin, wherein the maximum Sigma(θ) at θmax is greater than 35, θmax is between 20 and 60 degrees, and the minimum Sigma(θ) at θmin is between -10 and 10.

2. The optical filter of claim 1, wherein the filter has chromaticity measured under a D-65 illuminator, the distance between the chromaticity of the filter and the illuminator in the CIE 1931 2-degree color space is less than 0.0200, the correlated color temperature is greater than 4,500 K and less than 7,000 K, and the visible light transmittance is greater than 9% and less than 18%.

3. The optical filter according to claim 2, wherein the visible light transmittance is greater than 11% and less than 16%.

4. The optical filter of claim 1, wherein the filter has a chromaticity measured under a D-65 illuminator, the distance between the chromaticity of the filter and the illuminator in the CIE 1931 2-degree color space is less than 0.0200, the correlated color temperature is greater than 4,500 K and less than 7,000 K, and the visible light transmittance is greater than 18% and less than 40%.

5. The optical filter according to claim 4, wherein the visible light transmittance is greater than 22% and less than 29%.

6. The optical filter according to claim 4, wherein the visible light transmittance is greater than 24% and less than 27%.

7. The optical filter of claim 1, wherein the filter has chromaticity measured under a D-65 illuminator, the distance between the chromaticity of the filter and the illuminator in the CIE 1931 2-degree color space being less than 0.0200, wherein the filter reduces luminance by approximately 8 to 18% VLT, has a correlated color temperature between 4,500 and 7,000 K, a maximum saturation greater than 1.45 (45%) with an orientation between 20 and 40 degrees, and a minimum saturation between -1.05 and 1.05 (-5 and +5%) with an orientation substantially orthogonal to the angle of maximum saturation.

8. The optical filter of claim 1, wherein the filter has chromaticity measured under a D-65 illuminator, the distance between the chromaticity of the filter and the illuminator in the CIE 1931 2-degree color space being less than 0.0200, wherein the filter reduces luminance by approximately 18 to 40% VLT, has a correlated color temperature between 4,500 and 7,000 K, a maximum saturation greater than 1.45 (45%) with an orientation between 20 and 40 degrees, and a minimum saturation between -1.05 and 1.05 (-5 and +5%) with an orientation substantially orthogonal to the angle of maximum saturation.

9. The optical filter according to claim 1, wherein the filter has a polarizing element.

10. The optical filter of claim 1, wherein the minimum Sigma(θ) at θmin is between -10 and 10, and θmin is between 80 and 120 degrees.

11. An optical filter having a transmission spectrum that gives a maximum Sigma(θ) at θmax and a minimum Sigma(θ) at θmin, wherein the maximum Sigma(θ) at θmax is greater than 25, θmax is between 20 and 60 degrees, and the minimum Sigma(θ) at θmin is between -6 and 6.

12. The optical filter of claim 11, wherein the filter has chromaticity measured under a D-65 illuminator, the distance between the chromaticity of the filter and the illuminator in the CIE 1931 2-degree color space is less than 0.0200, and the correlated color temperature is greater than 4,500 K and less than 7,000 K, and the visible light transmittance is greater than 18% and less than 40%.

13. The optical filter of claim 12, wherein the visible light transmittance is greater than 22% and less than 29%.

14. The optical filter of claim 12, wherein the visible light transmittance is greater than 24% and less than 27%.

15. The optical filter of claim 11, wherein the filter has a chromaticity measured under a D-65 illuminant, the distance between the chromaticity of the filter and the illuminant in the CIE 1931 2-degree color space being less than 0.0200, wherein the filter reduces luminance by approximately 18 to 40% VLT, has a correlated color temperature between 4,500 and 7,000 K, a maximum saturation greater than 1.45 (45%) with an orientation between 20 and 40 degrees, and a minimum saturation between -1.05 and 1.05 (-5 and +5%) with an orientation substantially orthogonal to the angle of maximum saturation.

Images