hypso.calibration.correction module

hypso.calibration.correction.apply_radiometric_calibration(frame, exp, background_value, radiometric_calibration_coefficients)

Applies radiometric calibration. Assumes input is 12-bit values, and that the radiometric calibration coefficients are the same size as the input image. Note: radiometric calibration coefficients have original size (684,1080), matching the “normal” AOI of the HYPSO-1 data (with no binning).

Parameters:

  • frame (ndarray) – 2D frame to apply radiometric calibration

  • exp (float) – Exposure value

  • background_value (float) – Background value

  • radiometric_calibration_coefficients (ndarray) – 2D array of radio calibration coefficients

Returns:

Calibrated frame 2D array

hypso.calibration.correction.calibrate_cube(info_sat, raw_cube, correction_coefficients_dict)

Radiometrically Calibrate the Raw Cube (digital counts) to Radiance

Parameters:

  • info_sat (dict) – Dictionary containing capture information

  • raw_cube (ndarray) – Numpy array containing digital countes 3-channel cube

  • correction_coefficients_dict (dict) – Dictionary containing the 2D coefficients for correction

Returns:

Corrected 3-channel cube

Return type:

ndarray

hypso.calibration.correction.crop_and_bin_matrix(matrix, x_start, x_stop, y_start, y_stop, bin_x=1, bin_y=1)

Crops matrix to AOI. Bins matrix so that the average value in the bin_x number of pixels is stored.

Return type:

ndarray

hypso.calibration.correction.destriping_correct_cube(cube, correction_coefficients_dict)

Apply destriping correction matrix.

Parameters:

  • cube – 3-channel spectral cube

  • correction_coefficients_dict – Dictionary containing the 2D coefficients for destriping

Returns:

3-channel array for destriping correction

Return type:

ndarray

hypso.calibration.correction.get_coefficients_from_dict(coeff_dict, satobj)

Get the coefficients from the csv files contained in a dictionary.

Parameters:

  • coeff_dict (dict) – Dictionary containing the paths of the csv files to read

  • satobj – Hypso satellite object

Returns:

Dictionary containing the 2D coefficients read from the csv files

Return type:

dict

hypso.calibration.correction.get_coefficients_from_file(coeff_path)

Get correction coefficients from file

Parameters:

coeff_path (str) – Coefficient path to read (.csv)

Returns:

2D array of coefficients

Return type:

ndarray

hypso.calibration.correction.smile_correct_cube(cube, correction_coefficients_dict)

Run smile correction on each frame in a cube, using the center row in the frame as the reference wavelength/band for smile correction.

Parameters:

  • cube – 3-channel spectral cube

  • correction_coefficients_dict (dict) – Dictionary containing the coefficients for smile correction

Returns:

Return type:

ndarray

hypso.calibration.correction.smile_correction_one_frame(frame, spectral_band_matrix)

Run smile correction on each row in a frame, using the center row as the reference wavelength/band for smile correction.

Parameters:

  • frame – 2D frame on which to apply smile correction

  • spectral_band_matrix – Spectral coefficients (Wavelength)

Returns:

Corrected frame after smile correction

Return type:

ndarray

hypso.calibration.correction.smile_correction_one_row(row, w, w_ref)

Applies smile correction. Use cubic spline interpolation to resample one row onto the correct wavelengths/bands from a reference wavelength/band array to correct for the smile effect.

Parameters:

  • row – Data row to apply smile correction

  • w –

  • w_ref –

Returns:

Row corrected for smile effect

Return type:

ndarray