I got the error in the snippet. The Error message is given below. Kindly go through and rectify if possible. Thanks in Advance.

Error using chromadapt

The value of 'illuminant' is invalid. Expected input number 2, illuminant, to be one of these types:

single, double, uint8, uint16

Error in chromadapt>parseInputs (line 248)

parser.parse(varargin{:});

Error in chromadapt (line 154)

inputs = parseInputs(varargin{:});

Error in Untitled (line 15)

K = chromadapt(J,'Method','perez');

    clc
close 

% Reading the NIR band of a multispectral image
CIR = multibandread('paris.lan',[512, 512, 7],'uint8=>uint8', 128,'bil','ieee-le',{'Band','Direct',[4 3 2]});

% Applying decorrelation stretch to enhance image contrast
T = decorrstretch(CIR);

% Reducing haze from the stretched image
J = imreducehaze(T);

% Applying white balance to the stretched image
D65_illuminant = whitepoint('d65');
K = chromadapt(J,'Method','perez');

% D65_illuminant = im2double(D65_illuminant);
% K = chromadapt(J,'Method','simple','illuminant',D65_illuminant);

% K = chromadapt(J,'Method','simple','illuminant', whitepoint('d65'))

% Dehazing the white-balanced RGB image using the dark channel prior algorithm
L = darkChannelPrior(K);

% Converting the dehazed RGB image to HSV color space
M = rgb2hsv(L);

% Performing linear stretching on the S channel of the HSV image
M(:,:,2) = imadjust(M(:,:,2));

% Applying multi-scale retinex with white top-hat filtering on the V channel of the HSV image
M(:,:,3) = retinex_wthat(M(:,:,3), [15 80 250]);

% Converting the HSV image back to RGB color space
N = hsv2rgb(M);

% Applying Contrast Limited Adaptive Histogram Equalization (CLAHE) on the RGB image
O = adapthisteq(N,'ClipLimit',0.02,'Distribution','rayleigh');

% Displaying the original multispectral image and all the processed images
figure;
subplot(2,4,1); imshow(CIR); title('Original Multispectral Image');
subplot(2,4,2); imshow(T); title('Decorrelation Stretch');
subplot(2,4,3); imshow(J); title('Reduced Haze');
subplot(2,4,4); imshow(K); title('White Balance');
subplot(2,4,5); imshow(L); title('Dehazed (Dark Channel Prior)');
subplot(2,4,6); imshow(N); title('Retinex + HSV Conversion');
subplot(2,4,7); imshow(O); title('CLAHE');
sgtitle('Processed Images');

% Computing the Structural Similarity Index (SSIM) and Peak Signal to Noise Ratio (PSNR) between the original and dehazed images
ssim_val = ssim(CIR, L);
psnr_val = psnr(CIR, L);
fprintf('SSIM: %f\nPSNR: %f\n', ssim_val, psnr_val);

%% Define the missing functions
% Function for computing the dark channel prior of an RGB image
function J = darkChannelPrior(I, patch_size)
    if nargin < 2
        patch_size = 15;
    end
    hazy_img = double(I);
    hazy_gray = min(hazy_img, [], 3);
    J = ordfilt2(hazy_gray, 1, ones(patch_size, patch_size));
end

function V = retinex_wthat(V, scales)
%RETINEX_WTHAT Multi-scale retinex with white top-hat filtering.
%   V = RETINEX_WTHAT(V) applies multi-scale retinex with white top-hat 
%   filtering to the input image V. The function uses a set of pre-defined 
%   scales for the Gaussian blur and white top-hat filtering.
%
%   V = RETINEX_WTHAT(V, SCALES) applies multi-scale retinex with white
%   top-hat filtering using the scales specified in the input argument
%   SCALES. SCALES should be a vector containing the standard deviation
%   values for the Gaussian blur.
%
%   Example:
%       I = imread('lena.png');
%       V = rgb2gray(I);
%       V = im2double(V);
%       V = retinex_wthat(V);
%       imshow(V);
%
%   Reference:
%       Landini, G., and M. Randazzo. "A multi-scale Retinex for bridging
%       the gap between color images and the human observation of scenes."
%       Journal of Microscopy 207.2 (2002): 182-191.
%
%   See also IMTOPHAT, FSPECIAL, IMFILTER.

% Set default scales
if nargin < 2
    scales = [3 7 15];
end

% Apply multi-scale retinex
for i = 1:numel(scales)
    sigma = scales(i);
    hsize = 2 * ceil(2 * sigma) + 1;
    
    % Gaussian blur
    G = fspecial('gaussian', hsize, sigma);
    V_smooth = imfilter(V, G, 'symmetric');
    
    % White top-hat filtering
    SE = strel('disk', hsize, 0);
    V_wth = imtophat(V_smooth, SE);
    
    % Add filtered image to result
    V = V + V_wth;
end

% Normalize output
V = (V - min(V(:))) / (max(V(:)) - min(V(:)));
end

Answer 1

[Cris LaPierre]

Your syntax for calling chromdapt is incorrect. You must have either 2 inputs or 4, but you have 3 so 'Method' is being treated as the 2nd input (illuminant).

• B = chromadapt(A,illuminant)
• B = chromadapt(A,illuminant,Name,Value)