I have created a depth map using a time of flight sensor by measuring the distances to create a depth map I am not sure if it is correct.

clc;
clear all;
close all;
%% Step 1: Load the Data File
filePath = 'C:\Users\omeir\Downloads\time of flight data.csv'; % Update with the file path
data = readtable(filePath, 'VariableNamingRule', 'preserve');
% Extract relevant columns
Z = data.("Distance (mm)"); % Distance values
totalPoints = numel(Z); % Total number of data points
% Define target grid dimensions
M = 60; % Rows
N = 50; % Columns
New_L = M * N; % Total points required for reshaping
% Check if data needs padding or trimming
if totalPoints < New_L
    Z_padded = [Z; zeros(New_L - totalPoints, 1)]; % Pad with zeros
else
    Z_padded = Z(1:New_L); % Trim excess data
end
% Reshape depth data into a matrix
Z_matrix = reshape(Z_padded, [M, N]);
% Replace very small or invalid depth values
Z_matrix(Z_matrix < 50) = NaN; % Replace extremely small values with NaN
% Optional: Interpolate missing values
[X, Y] = meshgrid(1:N, 1:M); % Original grid
validMask = ~isnan(Z_matrix); % Mask of valid (non-NaN) points
Z_interpolated = griddata(X(validMask), Y(validMask), Z_matrix(validMask), X, Y, 'linear');
% Replace Z_matrix with interpolated data
Z_matrix = Z_interpolated;
%% Step 2: Visualize the Depth Map
figure;
surf(X, Y, Z_matrix, 'EdgeColor', 'none'); % Surface plot
shading interp; % Smooth shading
colormap('jet'); % Use a jet colormap
colorbar;
xlabel('X');
ylabel('Y');
zlabel('Depth');
title('Enhanced Depth Map');
view(3); % Set to 3D view               

I have used the following csv file. It will be helpful if you could give feedbacks.

Answer 1

[Mathieu NOE]

hello

the code seems correct but the look of the 3D plot seems 'maybe) questionnable . I had a feeling that the Z values below 1500 should be removed to get a smoother surface without the "holes" .

So I made this very basic change :

Z_matrix(Z_matrix < 1500) = NaN; % Replace extremely small values with NaN

shouldn't it be like this ?

%% Step 1: Load the Data File
filePath = 'C:\Users\omeir\Downloads\time of flight data.csv'; % Update with the file path
data = readtable(filePath, 'VariableNamingRule', 'preserve');
% Extract relevant columns
Z = data.("Distance (mm)"); % Distance values
totalPoints = numel(Z); % Total number of data points
% Define target grid dimensions
M = 60; % Rows
N = 50; % Columns
New_L = M * N; % Total points required for reshaping
% Check if data needs padding or trimming
if totalPoints < New_L
    Z_padded = [Z; zeros(New_L - totalPoints, 1)]; % Pad with zeros
else
    Z_padded = Z(1:New_L); % Trim excess data
end
% Reshape depth data into a matrix
Z_matrix = reshape(Z_padded, [M, N]);

% Replace very small or invalid depth values
% Z_matrix(Z_matrix < 50) = NaN; % Replace extremely small values with NaN
Z_matrix(Z_matrix < 1500) = NaN; % Replace extremely small values with NaN

% Optional: Interpolate missing values
[X, Y] = meshgrid(1:N, 1:M); % Original grid
validMask = ~isnan(Z_matrix); % Mask of valid (non-NaN) points
Z_interpolated = griddata(X(validMask), Y(validMask), Z_matrix(validMask), X, Y, 'linear');
% Replace Z_matrix with interpolated data
Z_matrix = Z_interpolated;
%% Step 2: Visualize the Depth Map
figure;
surf(X, Y, Z_matrix, 'EdgeColor', 'none'); % Surface plot
shading interp; % Smooth shading
colormap('jet'); % Use a jet colormap
colorbar;
xlabel('X');
ylabel('Y');
zlabel('Depth');
title('Enhanced Depth Map');
view(3); % Set to 3D view         

[Mathieu NOE]

A tiny code modification : the "small value removal" is done directly on the 1D data , instead of doing it after 2D conversion, and I added a tad of smoothing (if that is what you need) using smoothn available here :

smoothn - File Exchange - MATLAB Central

Result

code :

%% Step 1: Load the Data File
filePath = 'C:\Users\omeir\Downloads\time of flight data.csv'; % Update with the file path
data = readtable(filePath, 'VariableNamingRule', 'preserve');
% Extract relevant columns
Z = data.("Distance (mm)"); % Distance values
totalPoints = numel(Z); % Total number of data points

% Replace very small or invalid depth values
Z(Z < 1500) = NaN; % Replace extremely small values with NaN

% Define target grid dimensions
M = 60; % Rows
N = 50; % Columns
New_L = M * N; % Total points required for reshaping
% Check if data needs padding or trimming
if totalPoints < New_L
    Z_padded = [Z; zeros(New_L - totalPoints, 1)]; % Pad with zeros
else
    Z_padded = Z(1:New_L); % Trim excess data
end

% Replace very small or invalid depth values
Z_padded(Z_padded < 1500) = NaN; % Replace extremely small values with NaN

% Smooth a bit the data 
Z_padded = smoothn(Z_padded,10000);
% Fex : https://fr.mathworks.com/matlabcentral/fileexchange/25634-smoothn?requestedDomain=

% Reshape depth data into a matrix
Z_matrix = reshape(Z_padded, [M, N]);

% Optional: Interpolate missing values
[X, Y] = meshgrid(1:N, 1:M); % Original grid
validMask = ~isnan(Z_matrix); % Mask of valid (non-NaN) points
Z_interpolated = griddata(X(validMask), Y(validMask), Z_matrix(validMask), X, Y, 'linear');

% Replace Z_matrix with interpolated data
Z_matrix = Z_interpolated;
%% Step 2: Visualize the Depth Map
figure;
surf(X, Y, Z_matrix, 'EdgeColor', 'none'); % Surface plot
shading interp; % Smooth shading
colormap('jet'); % Use a jet colormap
colorbar;
xlabel('X');
ylabel('Y');
zlabel('Depth');
title('Enhanced Depth Map');
view(3); % Set to 3D view        

[Mathieu NOE]

hello again

problem solved ?