Output Documentation — Imatest Documentation

Currently, output documentation is limited to JSON outputs for Distortion and Sharpness, as well as stray light and concentric ring module results.

These preliminary descriptions of outputs do not yet cover results from all modules, and will be expanded to be more comprehensive going forward.

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Links to Documentation

- Output documentation fields (embedded below)
  - A searchable, filterable version is embedded below.
- Output documentation Excel spreadsheet
- Results from Stray Light and Concentric Rings

Embedded Output Documentation

Output documentation fields by module, snapshotted from the Imatest output-fields spreadsheet. Switch tabs below; each table scrolls and can be filtered. The complete data is included for print and offline use.

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Distortion

56 fields

JSON Field	SFR+	eSFR	CB	Type	Format	Units	Description	Equations		Online Documentation
X_center_shift_pxls	✓	✓	✓	int[]	1x1	pixels	The horizontal shift in pixels of the detected center of the chart from the geometric center of the image.
Y_center_shift_pxls	✓	✓	✓	int[]	1x1	pixels	The vertical shift in pixels of the detected center of the chart from the geometric center of the image.
radial_center_shift_pxls	✓	✓	✓	float[]	1x1	pixels	The radial shift in pixels of the detected center of the chart from the center of the image.
rotationDegrees	✓	✓	✓	float[]	1x1	degrees	Angle of the average image rotation.
chart_height_bar_bar_cm	✓			float[]	1x1	cm	User entry for SFRplus. The spacing between the black bars at the bottom and top of the target, measured directly from the chart.
bar_bar_vert_fraction	✓			float[]	1x1	Normalized	chart_height_bar_bar_cm normalized to the total image height.
bar_bar_vert_pixels	✓			float[]	1x1	pixels	chart_height_bar_bar_cm given in pixels.
mean_x_square_spacing_pxls	✓			float[]	1x1	pixels	The average horizontal distance between the centers of neighboring squares.
mean_y_square_spacing_pxls	✓			float[]	1x1	pixels	The average vertical distance between the centers of neighboring squares.
registration_mark_spacing_cm		✓		float[]	1x1	cm	The vertical distance between the centers of the registration marks present on the chart. Can average left and right pairs, but should be the same.
reg_reg_vert_fraction		✓		float[]	1x1	Normalized	The vertical distance between the centers of the registration marks, normalized to the image height.
reg_reg_vert_pixels		✓		float[]	1x1	pixels	The vertical distance between the centers of the registration marks given in pixels.
square_height_cm			✓	float[]	1x1	cm	User input; square height measured from target in cm.
square_vert_pixels			✓	float[]	1x1	pixels	Square height measured by Imatest given in pixels.
square_vert_fraction			✓	float[]	1x1	Normalized	Square height measured by Imatest, normalized to the full image height.	square_vert_pixels / HeightPxls
magnification_meas	✓	✓	✓	float[]	1x1	None	Magnification of the image on the image sensor relative to the object size. Requires using a target with known dimensions such as SFRplus, eSFR ISO, or Checkerboard, and entering the appropriate feature size on the target as well as the pixel pitch on the sensor.			docs ↗
FieldofView_DiagHV_cm	✓	✓	✓	float[]	1x3	cm	Image FOV in diagonal, horizontal, and vertical directions, respectively. Calculated using distortion fit coefficients and given in units of cm.
FieldofView_DiagHV_bar_bar_frac	✓			float[]	1x3		Measured FOV in the diagonal, horizontal, and vertical directions, respectively. Given in terms of how many times the active (bar-bar) height of the chart would fit across each image direction.	FieldofView_DiagHV_cm / chart_height_bar_bar_cm
FieldofView_DiagHV_reg_reg_frac		✓		float[]	1x3		Measured FOV in the diagonal, horizontal, and vertical directions, respectively. Given in terms of how many times the vertical distance between the registration would fit across each image direction.	FieldofView_DiagHV_cm / registration_mark_spacing_cm
FieldofView_DiagHV_square_count	✓		✓	float[]	1x3	# squares	Image FOV in diagonal, horizontal, and vertical directions, respectively. Calculated using distortion fit coefficients and given in terms of the number of squares visible across the FOV.	FieldofView_DiagHV_cm / square_height_cm
FieldofView_DiagHV_degrees	✓	✓	✓	float[]	1x3	degrees	Image FOV in diagonal, horizontal, and vertical directions, respectively. Calculated using distortion fit coefficients and given in units of degrees.
Pixel_aspect_ratio	✓	✓	✓	float[]	1x1		(Change in hoizontal FOV due to distortion) divided by (Change in vertical FOV due to distortion).	ΔFOV_h / ΔFOV_v
H_conv_angle_degrees	✓	✓	✓	float[]	1x1	degrees	The angle at which the horizontal lines in the image would intersect if extended far enough.
V_conv_angle_degrees	✓	✓	✓	float[]	1x1	degrees	The angle at which the vertical lines in the image would intersect if extended far enough.
lens_to_chart_distance_cm	✓	✓	✓	float[]	1x1	cm	Distance from the entrance pupil of the camera to the target. Entered by user in settings.
focal_lth_measured_mm	✓	✓	✓	float[]	1x1	mm	Focal length of the lens being used for testing. Entered by user or included in EXIF data.
SMIA_TV_Distortion_Pct	✓	✓	✓	float[]	1x1	%	TV distortion calculated using equations defined in the SMIA specification.		SMIA TV Distortion = 100(A - B)/B A = (A1 + A2)/2
ISO_TV_Distortion_Pct	✓	✓	✓	float[]	1x1	%	TV distortion calculated using equations from ISO 16505 standard.
k1_3rd_order_dist_coeff	✓		✓	float[]	1x1		Coefficient, k1, calculated for fit to 3rd order distortion model.	Standard:
								Division Model:
h1_h2_5th_order_dist_coeffs	✓		✓	float[]	1x2		Coefficients, k1, k2, calculated for fit to 5th order distortion model.	Standard:
								Division Model:
arctan_tan_dist_coeff	✓	✓	✓	float[]	1x1		Coefficient, p1, calculated for fit to arctan/tan disortion model.
distortion_coeffs_2nd_5th_All	✓		✓	float[]	1x4		Coefficients k_n for the "5th Order (ALL 2-5)" distortion calculation option. When this calculation option is not selected, the output for this field is always [0, 0].	Standard:
								Division Model:
x_distortion_decenter_ctrcor	✓			float[]	1x1	Normalized	Location of the horizontal center of distortion given relative to the horizontal center of the image. The normalization factor is the center-to-corner distance of the image. Positive values are to the right.
y_distortion_decenter_ctrcor	✓			float[]	1x1	Normalized	Location of the vertical center of distortion given relative to the vertical center of the image. The normalization factor is the center-to-corner distance of the image. Positive values are downward.
x_distortion_decenter_pixels	✓			float[]	1x1	pixels	Location of the horizontal center of distortion given relative to the horizontal center of the image. Positive values are to the right.
y_distortion_decenter_pixels	✓			float[]	1x1	pixels	Location of the vertical center of distortion given relative to the vertical center of the image. Positive values are downward.
x_distortion_decenter			✓	float[]	1x1	pixels	Location of the horizontal center of distortion given relative to the horizontal center of the image. Positive values are to the right.
y_distortion_decenter			✓	float[]	1x1	pixels	Location of the vertical center of distortion given relative to the vertical center of the image. Positive values are downward.
distortion_decenter_norml			✓	float[]	1x2	Normalized	[x, y] locations of the center of distortion given relative to the vertical center of the image. Positive values are downward and to the right. The normalization factor is output in radius_norml_factor_px.
max_detected_radius_norml			✓	float[]	1x1	Normalized	The normalized radius of the farthest detected checker saddle point from the center. All distortion paramters/measurements above this radius are extrapolated. The smaller this is the less reliable distortion measurements are. The normalization factor is output in radius_norml_factor_px.
radius_norml_factor_px			✓	float[]	1x1	pixels	The radius in pixels used to normalize distortion distances. If no image circle is used, then this is the center-corner distance.
best_distortion_calculation	✓		✓	string			Human readable output indicating which distortion model returned the best fit.
image_circle_method			✓	string			The user-provided method for computing the image circle. One of: "None", "Specify radius (px) from image center", or "Specify radius and center".
image_circle_params			✓	float[]	1x3	pixels	The image circle parameters: center x, center y, radius. This does not appear in the results unless image_circle_method is not None. The center location is in IEEE Std 2020:2024 Type IV image coordinates (one indexed from upper-left).
distortion_coefficients	✓		✓	float[]	1xn_coeffs		The distortion coefficients corresponding to best_distortion_calculation. n_coeffs = the number of coefficients required for the best fit equation.
radius	✓		✓	float[]	1x11	Normalized	Normalized radii of points, r, in distorted (input) image The normalization factor is output in radius_norml_factor_px.
radius_undistorted	✓		✓	float[]	1x11	Normalized	Normalized radii of points, r', in undistorted (distortion corrected) image The normalization factor is output in radius_norml_factor_px.
Delta_radius	✓		✓	float[]	1x11	Normalized	The change in radius, Δr, between points in the distorted (input) image and the undistorted (distortion corrected) image. The normalization factor is output in radius_norml_factor_px.	Δr = r - r' = radius - radius_undistorted
lens_geometric_distortion_pct	✓		✓	float[]	1x11	%	Lens Geometric Distortion (LGD), which is included in the CPIQ Phase 2 specification, and is equivalent to Optical Distortion (defined by Edmund Optics).	LGD = 100x(Delta_radius/radius_undistorted)
max_geometric_distortion_pct	✓		✓	float[]	1x1	%	Maximum value in lens_geometric_distortion_pct.
min_geometric_distortion_pct	✓		✓	float[]	1x1	%	Minimum value in lens_geometric_distortion_pct.
worst_geometric_distortion_pct	✓		✓	float[]	1x1	%	Absolute value of min_geometric_distortion_pct.
chart_angle_from_circles_degrees			✓	float[]	1x1	degrees	Angle of the checkerboard chart derived from the chart center circles. Represents the angle of the horizontal arm of an upside-down "L" shape circle pattern, relative to the x-axis of the image. Clockwise rotations are reported as positive angles (-180 to 180).

Sharpness

170 fields

JSON Field	SFR	SFR+	eSFR	reg	CB	LFC	Wedge	Rand	Star	Type	Format	Units	Description	Equations	Online Documentation
EDGE MTF
angle_from_tangential_sfr_deg		✓	✓	✓	✓					float[]	1xN_roi	degrees	Angle away from tangential sfr (radial edge). Radial edges (tangential sfr) will have values close to 0. Tangential edges (saggital SFR) will have values close to 90. The angle is measured between the image-center-to-edge-center vector and the edge vector.
apply_MTF_compensation_deconv	✓					✓		✓	✓	int[]	1x1	None	Indicates whether or not the user has selected to apply MTF compensation. 0 = No 1 = Yes
mtfPeak	✓	✓	✓	✓	✓					float[]	1xN_roi	cycles/pixel	The maximum MTF value for each selected edge. Values are normalized to the low-frequency value for each individual MTF measurement.
mtfnn	✓	✓	✓	✓	✓					float[]	1xN_roi	cycles/pixel	Frequency value where MTF = nn% of 1 for each selected edge. nn = 50, 30, 20, 10
mtfnnp	✓	✓	✓	✓	✓					float[]	1xN_roi	cycles/pixel	Frequency value where MTF = nn% of its maximum for each selected edge. nn = 50, 30, 20, 10
MTF_user_units	✓		✓	✓	✓				✓	object			Gives MTF results in frequency_units, selected by user.
frequency_units	✓		✓							string	"<units>"	user selected	Indicates MTF frequency units selected by user.
secondary_readout_n	✓	✓	✓	✓	✓			✓	✓	string		None	Human readable description of selected secondary readout.
secondary_n_results	✓	✓	✓	✓	✓			✓	✓	float[]	1xN_roi	user selected	Results of selected secondary readout for each ROI.
secondary_n_min_max_ratio		✓	✓	✓	✓					float[]	1x1		The ratio of the minimum to maximum values in secondary_n_results.
quadrants		✓	✓	✓	✓					string		None	Divides the test chart up into 5 sections where the regions that fall into those sections are averaged, including Center, UR, LR, UL, LL.		docs ↗
secondary_n_quadrant_mean		✓	✓	✓	✓					float[]	1x5		The mean value of the secondary readout for each quadrant.
secondary_n_quadrant_min		✓	✓	✓	✓					float[]	1x5		The minimum value of the secondary readout for each quadrant.
secondary_n_quadrant_min_location		✓	✓	✓	✓					string	"quadrant"	None	The quadrant containing secondary_n_quadrant_min. Possible values: "Center", "UR", "LR", "UL", "LL"
secondary_n_quadrant_max		✓	✓	✓	✓					float[]	1x5		The maximum value of the secondary readout for each quadrant.
secondary_n_quadrant_max_location		✓	✓	✓	✓					string	"quadrant"	None	The quadrant containing secondary_n_quadrant_max. Possible values: "Center", "UR", "LR", "UL", "LL"
riseLevelsPct	✓	✓	✓	✓	✓					string	"nnnn"	%	Gives lower and upper limits of rise distance calculation Example: "1090" --> 10-90% of the edge spread function.
riseDistPxls	✓	✓	✓	✓	✓					float[]	1xN_roi	pixels	X-distance between the upper and lower y-limits set by riseLevelPct, given for each edge.
edgeRoughnessSTD	✓	✓	✓	✓	✓					float[]	4xN_roi		Total edge roughness (STD) measurement for each color channel (row) and ROI (column). Color channel order = RGBY		docs ↗
overSharpeningPct	✓	✓	✓	✓	✓			✓		float[]	1xN_roi	%	The amount of sharpening relative to standardized sharpening, which results in a modest amount of overshoot, similar to what you might get after manually sharpening the image. Undersharpening is displayed here as a negative number. Note that this is a measurement made in the frequency domain.
overshootPct	✓	✓	✓	✓	✓					float[]	1xN_roi	%	Measurement of the "bump" in the edge profile caused by sharpening. Note that this is a measurement made in the spatial domain.	100 * (esf_max - pixel_level_light) / pixel_level_light esf = edge spread function We calculate this with normalized data as: 100 * (esf_max_norm - 1) [This data is "normalized" as: pixel_level_light = 1, pixel_level_dark = 0]	docs ↗
undershootPct	✓	✓	✓	✓	✓					float[]	1xN_roi	%	Measurement of the "dip" in the edge profile caused by sharpening. Note that this is a measurement made in the spatial domain.	100 * (pixel_level_dark - esf_min) / pixel_level_dark esf = edge spread function We calculate this with normalized data as: -100 * (esf_min_norm) [This data is "normalized" as: pixel_level_light = 1, pixel_level_dark = 0]
LineSpreadFn_PW50_Pxls	✓	✓	✓	✓	✓					float[]	1xN_roi	pixels	"Pulse width 50", equivalent to "Full width at half maximum" (FWHM).
edge_angle_degrees	✓	✓	✓	✓	✓					float[]	1xN_roi	degrees	The angle of the edge with respect to perfectly horizontal or vertical.
pixel_level_light	✓	✓	✓	✓	✓					float[]	1xN_roi	DN (255)	Pixel level at which the edge response curve plateaus on the bright side.		docs ↗
pixel_level_dark	✓	✓	✓	✓	✓					float[]	1xN_roi	DN (255)	Pixel level at which the edge response curve plateaus on the dark side.
pixel_level_ratio	✓	✓	✓	✓	✓					float[]	1xN_roi	None	pixel_level_light / pixel_level_dark for each ROI.
pixel_level_ratio_mean	✓	✓	✓	✓	✓					float[]	1x1	None	pixel_level_light / pixel_level_dark averaged over all ROIs.
mtf50asym_x_y_Pct		✓	✓	✓	✓					float[]	1x2	%	MTF asymmetry is calculated in the x (horizontal) and y (vertical) directions. MTF50 as functions of x and y are fitted to second-order (parabolic) curves, which are used to calculate expected MTF50 values at the Top, Bottom, Left and Right (MTF50T, etc.) of the image.	MTF asymmetry (x) = (MTF50R-MTF50L) / (MTF50R+MTF50L) MTF asymmetry (y) = (MTF50T-MTF50B) / (MTF50T+MTF50B)	docs ↗
mtf_center_loc_Pct		✓	✓	✓	✓					float[]	1x2	%	The location of the center of focus in the horizontal (x) and vertical (y) directions, respectively. Given as percentages of the full image width and height, respectively.	(mtf_center_loc_Pixels[1] / WidthPxls ) * 100, (mtf_center_loc_Pixels[2] / HeightPxls) * 100
mtf_center_loc_Pixels		✓	✓	✓	✓					float[]	1x2	pixels	The location of the center of focus in the horizontal (x) and vertical (y) directions, respectively. Given as the pixel index.
freq1units	✓									string	"<units>"	user selected	User selected frequency units in human-readable form.
freq2units	✓									string	"<units>"	user selected	User selected frequency units in human-readable form.
freq1	✓									float[]	1x637	user selected	Frequency values corresponding to freq1units.
freq2	✓									float[]	1x637	user selected	Frequency values corresponding to freq2units.
mtf_nchan	✓									float[]	1x637	None	MTF values for primary channel selected by user.
mtf_r	✓									float[]	1x637	None	Red channel MTF.
mtf_g	✓									float[]	1x637	None	Green channel MTF.
mtf_b	✓									float[]	1x637	None	Blue channel MTF.
mtf_y	✓									float[]	1x637	None	Luminance channel MTF.
MTFfreq_CP	✓	✓	✓	✓	✓					float[]	1x31	cycles/pixel	Frequency values in units of cycles/pixel. Same frequencies are always used.
MTF_Interpolated	✓	✓	✓	✓	✓					float[]	N_roi x31	None	- Interpolated MTF data for the primary color channel selected by user. - Will always duplicate one of the MTFinterpn arrays.
mtf_diff_ltd_freq	✓		✓							float[]	1x221		Frequency values for diffraction-limited MTF calculation.
mtf_diff_ltd	✓		✓							float[]	1x221		Diffraction-limited MTF. - This is a theoretical limit, not a measurement. - Must enter pixel size and aperture information to get this output.
freq_ois	✓	✓	✓	✓	✓					float[]	1x61		Frequency values for mtf_ois.
mtf_ois	✓	✓	✓	✓	✓					float[]	N_roi x61		MTF related to optical image stabilization.
MTFinterpn	✓	✓	✓	✓	✓					float[]	N_roi x31	None	- MTF data for the R, G, B, and Y channels respectively. - Measured MTF curve interpolated to report values at frequencies given by MTFfreq_CP.
rnnnnPxls	✓	✓	✓	✓	✓					float[]	1x1	pixels	- Rise distance in pixels (measured from edge profile). - nnnn = 1090 indicates a rise distance measured between 10% and 90% of the dark/light plateau values.
linearization_method	✓	✓	✓	✓	✓					string	1x1	None	The user-selected method for linearizing the slanted-edge ROI image data for SFR calculations. Also used for linearizing any wedge ROI data for SFR calculations.
linearization_required_extrap_edge	✓	✓	✓	✓	✓					int[]	1 x N_edge_rois	None	- List of logical (1 or 0) indicating whether each edge ROI required extrapolation of the LUT when linearizing the image data. - This field only appears when the linearization_method is "Linearly interpolated LUT from step chart".
linearization_required_extrap_wedge	✓	✓	✓	✓	✓					int[]	1 x N_wedge_groups	None	- List of logical (1 or 0) indicating whether each wedge ROI required extrapolation of the LUT when linearizing the image data. - This field only appears when the linearization_method is "Linearly interpolated LUT from step chart".
MTF SUMMARY
region_weights	✓	✓	✓	✓	✓					float[]	1x3	fractional %	Weights applied to values from central, inner, and outter regions respectively for summary results (e.g. mean MTF50).
summaryRegions		✓	✓	✓	✓					string			Labels for entries in "summary" results below.
mtf_summary_specified_units		✓	✓	✓	✓					string	"<units>"		MTF units selected by user.
mtfnn_CP_summary		✓	✓	✓	✓					float[]	1x11	cycles/pixel	Frequency value where MTF = nn% of 1, for slanted-edges. Values correspond to summaryRegions.
mtfnn_specified_units_summary		✓	✓	✓	✓					float[]	1x11	user selected
mtfnn_LWPH_summary		✓	✓	✓	✓					float[]	1x11	LW/PH
mtfnn_CP_wedge_summary			✓							float[]	1x11	cycles/pixel	Frequency value where MTF = nn% of 1, for wedges. Values correspond to summaryRegions.
mtfnn_specified_units_wedge_summary			✓							float[]	1x11	user selected
mtfnnp_CP_summary		✓	✓	✓	✓					float[]	1x11	cycles/pixel	Frequency value where MTF = nn% of its maximum, for slanted-edges. Values corresponds to summaryRegions.
mtfnnp_specified_units_summary		✓	✓	✓	✓					float[]	1x11	user selected
mtfnnp_LWPH_summary		✓	✓	✓	✓					float[]	1x11	LW/PH
mtfnnP_CP_wedge_summary			✓							float[]	1x11	cycles/pixel	Frequency value where MTF = nn% of its maximum, for wedges. Values corresponds to summaryRegions.
mtfnnP_specified_units_wedge_summary			✓							float[]	1x11	user selected
riseDistPxls_summary		✓	✓	✓	✓					float[]	1x11	pixels	The 10-90% rise distance values corresponding to summaryRegions.
riseDist_PH_summary		✓	✓	✓	✓					float[]	1x11	% picture height
overSharpening_Pct_summary		✓	✓	✓	✓					float[]	1x11	%	overSharpeningPct results corresponding to summaryRegions.
overshoot_Pct_summary		✓	✓	✓	✓					float[]	1x11	%	overshootPct results corresponding to summaryRegions.
secondary_n_summary		✓	✓	✓	✓					float[]	1x11	User selected	Secondary readout results corresponding to summaryRegions.
edgeRoughSTD_summary		✓	✓	✓	✓					float[]	1x11		Total edge roughness (STD) measurement for Y-channel.
MTF_Area_PkNorm_summary		✓	✓	✓	✓					float[]	1x11		Area under the MTF curve (below the Nyquist frequency), normalized to its peak value. Values correspond to summaryRegions.
mean_ROI_summary		✓	✓	✓	✓					float[]	1x11		Mean normalized pixel level for selected ROIs.
peakMTF_summary		✓	✓	✓	✓					float[]	1x11	None	Maximum MTF values corresponding to summaryRegions. Values are normalized to the low-frequncy value for each individual MTF measurement.
LSF_PW50_pxls_summary		✓	✓	✓	✓					float[]	1x11	pixels	The width of the line spread function at 50% of its maximum value. Values correspond to summarRegions.
Non-Edge MTF
row						✓				int[]	1x23	None	Indices of horizontal rows 1-23 used for calculation.
contrast						✓				float[]	1x23		Low frequency contrast for MTFnn plot.
MTFnn_Cycles_per_Pixel						✓	✓	✓	✓	float[]	1x23, 1xN_wedge, 1xN_segments	cycles/pixel	The frequency at which the MTF reaches nn% of the low frequency value.
MTFnnP_Cycles_per_Pixel						✓	✓	✓	✓	float[]	1x23, 1xN_wedge, 1xN_segments	cycles/pixel	The frequency at which the MTF reaches nn% of the peak MTF value.
freq_CP_row_n						✓				float[]	1x269	cycles/pixel	Frequency values for MTF_smooth_row_n. n = 1, 4, 7, 10, 13, 16, 19
MTF_smooth_row_n						✓				float[]	1x269	None	Smoothed MTF values for each analysis row given by "n". n = 1, 4, 7, 10, 13, 16, 19
max_detected_frequency_Cycles_per_Pixel						✓	✓	✓	✓	float[]	1x1	cycles/pixel	The maximum measurable frequency detected in the test image.
frequency_Cycles_per_Pixel								✓		float[]		cycles/pixel	Frequency values for MTF & MTF_with_noise.
MTF_for_segments								✓		float[]	N_segments x length(frequency_Cycles_per_Pixel)		The MTF curve data for each chart segment measured. The number of segments is selected by the user in the "More settings" window.
MTF								✓		float[]	1xlength(frequency_Cycles_per_Pixel)	None	Noise-subtracted MTF values corresponding to frequency_Cycles_per_Pixel.
MTF_with_noise								✓		float[]	1xlength(frequency_Cycles_per_Pixel)	None	MTF values with noise (without noise-subtraction) correspondning to frequency_Cycles_per_Pixel.
noise_PSD								✓		float[]	1xlength(frequency_Cycles_per_Pixel)		Power Spectral Density calculated from flat gray regions on the sides of the Spilled Coins target.		docs ↗
signal_plus_noise_PSD								✓		float[]	1xlength(frequency_Cycles_per_Pixel)		Power Spectral Density calculated from the texture pattern region of the Spilled Coins target.
signal_PSD								✓		float[]	1xlength(frequency_Cycles_per_Pixel)		The difference between signal_plus_noise_PSD and noise_PSD.	signal_plus_noise_PSD - noise_PSD	docs ↗
number_of_radii									✓				Number of radii to use for calculation. Selected by user.
segments_total									✓	int[]	1x1	None	Number of segments used for calculation. Set by user in "More settings" window.
segments_valid									✓	int[]	1xN_vs	None	Lists each segment considered valid for use in calculations. N_vs = Number of valid segments. Can range from 0-segments_total.
frequency_C_P									✓	float[]	1xnumber_of_radii	cycles/pixel	The frequency of the star pattern at each radius measured.
freq_interp_C_P									✓	float[]	1x51	cycles/pixel	Interpolated frequency values calculated using values in frequency_C_P.
MTF_unsmoothed_mean									✓	float[]	1xN_radii	None	MTF values corresponding to frequency_C_P. Averaged over all segments.
MTF_interp_smooth_mean									✓	float[]	1x51	None	MTF values corresponding to freq_interp_C_P. Averaged over all segments.
MTF_interp_smooth_segments									✓	float[]	N_segments x51	None	MTF values corresponding to freq_interp_C_P for each chart segment analyzed.
WEDGE
moire_measurement			✓							string			The moire measurement method (color difference) selected by the user.
moire_smoothing			✓							string			Indicates whether or not smoothing has been applied.
wedge_number			✓							int[]	1xN_wedge		Indices for wedge groups. Each wedge group consists of one high frequency wedge and one low frequency wedge.
MTFnn_wedge_Cycles_per_Pixel			✓							float[]	1xN_wedge	cycles/pixel	The frequency at which the MTF reaches nn% of the low frequency value, for each wedge group analyzed.
MTFnnP_wedge_Cycles_per_Pixel			✓							float[]	1xN_wedge	cycles/pixel	The frequency at which the MTF reaches nn% of the peak MTF value, for each wedge group analyzed.
*_freq_wedge_center_locations_x			✓							float[]	1xN_wedge	pixels	The locations of the centers of each wedge ROI. x = horizontal, y = vertical, corner_pct = radial * = "low", "high"
*_freq_wedge_center_locations_y			✓							float[]	1xN_wedge	pixels
*_freq_wedge_center_corner_pct			✓							float[]	1xN_wedge	% ctr-corner
*_freq_wedge_boundary_x_left			✓							float[]	1xN_wedge	pixels	The x, y boundaries of each wedge ROI. * = "low", "high" y_top \| - - - \| x_left \| \| x_right \| - - - \| y_bot
*_freq_wedge_boundary_x_right			✓							float[]	1xN_wedge	pixels
*_freq_wedge_boundary_y_top			✓							float[]	1xN_wedge	pixels
*_freq_wedge_boundary_y_bot			✓							float[]	1xN_wedge	pixels
aliasing_onset_smoothed_CPP			✓				✓			float[]	1xN_wedge	cycles/pixel	The spatial frequency where the (un)smoothed count of bars drops below 95% of the low frequency count.
aliasing_onset_unsmoothed_CPP			✓				✓			float[]	1xN_wedge	cycles/pixel
aliasing_onset_sm_CPP_mean_1_4			✓							float[]	1x1	cycles/pixel	Mean of aliasing_onset_smoothed_CPP for the first four wedge groups only.
aliasing_onset_sm_CPP_mean_all			✓							float[]	1x1	cycles/pixel	Mean of aliasing_onset_smoothed_CPP.
moire							✓			float[]	1x317		The color difference selected by the user, indicated by moire_measurement, given for all measured frequencies of each wedge.		docs ↗
moire_spread_near_Nyq			✓				✓			float[]	1xN_wedge		Measures the amplitude (spread) of moiré artifacts in the frequency band near the Nyquist limit (where aliasing is most likely) for each wedge.
color_aliasing_max_mean_R_minus_B			✓				✓			float[]	1xN_wedge		the worst-case moiré color artifact of the Red channel minus the Blue channel for eachwedge, which can be used for reporting, plotting, or further analysis of color artifacts in the test chart image.
color_aliasing_max_mean_R_minus_B_normalized			✓				✓			float[]	1xN_wedge		the worst-case moiré color artifact of the Red channel minus the Blue channel for eachwedge, which can be used for reporting, plotting, or further analysis of color artifacts in the test chart image, normalized between 0-1.
color_aliasing_max_mean_R_minus_G			✓				✓			float[]	1xN_wedge		the worst-case moiré color artifact of the Red channel minus the Green channel for eachwedge, which can be used for reporting, plotting, or further analysis of color artifacts in the test chart image.
color_aliasing_max_mean_R_minus_G_normalized			✓				✓			float[]	1xN_wedge		the worst-case moiré color artifact of the Red channel minus the Green channel for eachwedge, which can be used for reporting, plotting, or further analysis of color artifacts in the test chart image, normalized between 0-1.
color_aliasing_max_mean_G_minus_B			✓				✓			float[]	1xN_wedge		the worst-case moiré color artifact of the Green channel minus the Blue channel for eachwedge, which can be used for reporting, plotting, or further analysis of color artifacts in the test chart image.
color_aliasing_max_mean_G_minus_B_normalized			✓				✓			float[]	1xN_wedge		the worst-case moiré color artifact of the Green channel minus the Blue channel for eachwedge, which can be used for reporting, plotting, or further analysis of color artifacts in the test chart image, normalized between 0-1.
iqkpi_metric			✓				✓			string[]	N_wedge x2	cycles/pixel	This method estimates image resolution by analyzing Y-channel resolution wedges and counting distinguishable lines in image rows and columns using gradient-based thresholds, with final resolution defined by where a set number of lines become indistinguishable due to merging. Output is in cycles/pixels.		docs ↗
iqkpi_LPH			✓				✓			string[]	N_wedge x2	LW/PH	The above iqkpi_metric in units of Line Widths per Picture Height.
frequency_Cycles_per_Pixel							✓			float[]	1x317	cycles/pixel	Frequency values for MTF_smooth & MTF_orig.
MTF_orig							✓			float[]	1x317	None	MTF curve data corresponding to frequency_Cycles_per_Pixel.
MTF_smooth							✓			float[]	1x317	None	Smoothed MTF curve data corresponding to frequency_Cycles_per_Pixel.
fraction_bars_smooth							✓			float[]	1x317	None	Fraction of the total number of bars that are detectable at each measured frequency after smoothing.
fraction_bars							✓			float[]	1x317	None	Fraction of the total number of bars that are detectable at each measured frequency.
Acutance & SQF
print_height_for_SQF		✓	✓	✓	✓					float[]	1x100	cm	The print height corresponding to each value in the SQF output, below. For a fixed print height and varying viewing distance, all values in this output will be the same.		docs ↗
viewing_distance_for_SQF		✓	✓	✓	✓					float[]	1x100	cm	The viewing distance corresponding to each value in the SQF output, below. For a fixed viewing distance and varying print height, all values in this output will be the same.
SQF		✓	✓	✓	✓					float[]	1x100		The subjective quality factor results corresponding to each print_height_for_SQF and viewing_distance_for_SQF result given above.
print_height_cm						✓		✓	✓	float[]	1xN	cm	The array of print height(s) in cm used to calculate each value in sqf_calculation. Note either this or viewing_distance_cm will be constant.
viewing_distance_cm						✓		✓	✓	float[]	1xN	cm	The array of viewing distance(s) in cm used to calculate each value in sqf_calculation. Note either this or print_height_cm will be constant.
readout_picture_height_cm						✓		✓	✓	float[]	1x1	cm	The user-provided readout picture height in cm.
readout_viewing_distance_cm						✓		✓	✓	float[]	1x1	cm	The user-provided readout viewing distance in cm.
readout_type						✓		✓	✓	string			The calculation type selected by the user in the Acutance & SQF settings window.
readout_value						✓		✓	✓	float[]	1x1		The value of the calculation defined in readout_type at the "Readout" height/distance set by the user.
acutance_readout						✓		✓	✓	string			A human readable string that summarizes the readout_value actuance calculation.
sqf_calculation_type						✓		✓	✓	string			The calculation type selected by the user in the Acutance & SQF settings window.
SQFregion						✓		✓	✓	string			The chart region used for the acutance calculation.
sqf_calculation						✓		✓	✓	float[]			Results of the SQF calculation for each picture height/viewing distance.
sqf_normalization						✓		✓	✓	string			String that provides information on the normalization method selected by the user in the Acutance & SQF settings.
EDGE Information Capacity

edge_info_note1	✓	✓	✓	✓	✓					string	1x1		"Information capacity results. For color images, channels are R G B Y".
edge_info_signal_V_P_P	✓	✓	✓	✓	✓					float[]	n_channels x n_roi		Peak to peak voltage (sqrt of power) of the slanted edge signal.
edge_info_noise_V_RMS	✓	✓	✓	✓	✓					float[]	n_channels x n_roi		Root mean square of the slanted edge signal. Output includes value for each color channel (e.g., RGBY) and each edge ROI.
edge_info_snr_RMS	✓	✓	✓	✓	✓					float[]	n_channels x n_roi		Root mean square of slanted edge SNR. Output includes value for each color channel (e.g., RGBY) and each edge ROI.
edge_info_capacity_C_4_b_p	✓	✓	✓	✓	✓					float[]	n_channels x n_roi	bits/pixel	Information capacity of a 4:1 contrast edge. Calculated from SNR. Measured in bits/pixel.
edge_info_capcity_C_max_b_p	✓	✓	✓	✓	✓					float[]	n_channels x n_roi	bits/pixel	Information capacity if the entire dynamic range of the camera is utilized. Calculated from SNR. Measured in bits/pixel.
edge_info_capacity_C_4_NEQ_b_p	✓	✓	✓	✓	✓					float[]	n_channels x n_roi	bits/pixel	Information capacity of a 4:1 contrast edge. Calculated from noise equivalent quanta measurements (NEQ). Measured in bits/pixel.
edge_info_capacity_C_max_NEQ_b_p	✓	✓	✓	✓	✓					float[]	n_channels x n_roi	bits/pixel	Information capacity if the entire dynamic range of the camera is utalized. Calculated from noise equivalent quanta measurements (NEQ). Measured in bits/pixel.
signal_averages_for_info	✓	✓	✓	✓	✓					float[]	1x1		Noise reduction at edge via signal averaging.
edgeInfoCapactyMax_total_Mb	✓	✓	✓	✓	✓					float[]	1x1		Total C_max in megabits.
edge_info	✓	✓	✓	✓	✓					struct	nrois x 1
{
ROI	✓	✓	✓	✓	✓					string	1x1		Region of interest index.
Channels	✓	✓	✓	✓	✓					string	n_channels x 1		Channel labels.
frequency_dependent	✓	✓	✓	✓	✓					struct	4x1
{
frequency	✓	✓	✓	✓	✓					float[]	1 x n_freq	C/P	Frequency in secondary readout units. Default is cycles per pixel.
Noise_Voltage_Spectrum	✓	✓	✓	✓	✓					float[]	n_channels x n_freq	signal / sqrt(hz)	Square root of noise power spectrum. Measured in [signal]/sqrt(Hz).
Noise_Power_Spectrum	✓	✓	✓	✓	✓					float[]	n_channels x n_freq	signal.^2 / hz	Noise power at a slanted edge as a function of frequency. Measured in [signal].^2 / Hz.
Noise_Equivalent_Quanta	✓	✓	✓	✓	✓					float[]	n_channels x n_freq	Number of quanta, or photons	Frequency dependent signal to noise ratio. Measured in number of quanta, or photons.
}
Edge_Voltage	✓	✓	✓	✓	✓					struct	2x1
{
pixels	✓	✓	✓	✓	✓					float[]	1 x n_pixels (not image pixels)		Slanted edge roi coordinate.
Edge_Voltage_unnormalized	✓	✓	✓	✓	✓					float[]	n_channles x n_pixels		Slanted edge signal of the unbinned image.
}
Autocorrelation	✓	✓	✓	✓	✓					struct	2x1
{
pixels	✓	✓	✓	✓	✓					float[]	1 x 11		Spatial position seperation between two correlation points of the noise power spectrum across a slanted edge.
Noise_Autocorrelation	✓	✓	✓	✓	✓					float[]	n_channels x 11		Similarity between noise power across a slanted edge as a function of spatial position difference. Calculated as the absolute value of the inverse fourier transform of noise voltage spectrum (via the Wiener-Khinchen theorem).
}
SNRi	✓	✓	✓	✓	✓					struct	3x1
{
box_width	✓	✓	✓	✓	✓					float[]	1 x 10	pixels	Size of small object. Measured in pixels.
SNRi_square	✓	✓	✓	✓	✓					float[]	n_channels x 10		Measure of detectability of a square of size w x w.
SNRi_rectangle	✓	✓	✓	✓	✓					float[]	n_channels x 10		Measure of detectability of a rectangle of size w x 4w.
}
}

Change Log

4 fields

Update	Sheet	Field Name	Description	Old Field Name	Old Description
change field	Sharpness	readout_picture_height_cm	The user-provided readout picture height in cm.	picture_ht_cm	The value set for the fixed picture height.
new field	Sharpness	readout_viewing_distance_cm	The user-provided readout viewing distance in cm.
update description	Sharpness	print_height_cm	The array of print height(s) in cm used to calculate each value in sqf_calculation. Note either this or viewing_distance_cm will be constant.		Print height values used to calculate each value in sqf_calculation. When using fixed print height, all values in this array will be the same.
update description	Sharpness	viewing_distance_cm	The array of viewing distance(s) in cm used to calculate each value in sqf_calculation. Note either this or print_height_cm will be constant.		The value set for the fixed viewing distance.