function [ img ] = Ptcloud2ScanContext( ptcloud, num_sector, num_ring, max_range )

%% Preprocessing 

% Downsampling for fast search
gridStep = 0.5; % 0.5m cubic grid downsampling is applied in the paper. 
ptcloud = pcdownsample(ptcloud, 'gridAverage', gridStep);

% point cloud information 
num_points = ptcloud.Count;
gap = max_range / num_ring; 
angle_one_sector = 360/num_sector;


%% vacant bins 
cell_bins = cell(num_ring, num_sector);
cell_bin_counter = ones(num_ring, num_sector);

enough_large = 500; % for fast and constant time save, We contain maximum 500 points per each bin.
enough_small = -10000;
for ith_ring = 1:num_ring
   for ith_sector = 1:num_sector
        bin = enough_small * ones(enough_large, 3);
        cell_bins{ith_ring, ith_sector} = bin;
   end
end


%% Save a point to the corresponding bin 
for ith_point =1:num_points

    % Point information 
    ith_point_xyz = ptcloud.Location(ith_point,:);
    ith_point_r = sqrt(ith_point_xyz(1)^2 + ith_point_xyz(2)^2);
    ith_point_theta = XY2Theta(ith_point_xyz(1), ith_point_xyz(2)); % degree
    
    % Find the corresponding ring index 
    tmp_ring_index = floor(ith_point_r/gap);
    if(tmp_ring_index >= num_ring)
        ring_index = num_ring;
    else
        ring_index = tmp_ring_index + 1;
    end
    
    % Find the corresponding sector index 
    tmp_sector_index = ceil(ith_point_theta/angle_one_sector);
    if(tmp_sector_index == 0)
        sector_index = 1;
    elseif(tmp_sector_index > num_sector || tmp_sector_index < 1)
        sector_index = num_sector;
    else
        sector_index = tmp_sector_index;
    end
    
    % Assign point to the corresponding bin cell 
    try
        corresponding_counter = cell_bin_counter(ring_index, sector_index); % 1D real value.
    catch
        continue;
    end
    cell_bins{ring_index, sector_index}(corresponding_counter, :) = ith_point_xyz;
    cell_bin_counter(ring_index, sector_index) = cell_bin_counter(ring_index, sector_index) + 1; % increase count 1
    
end


%% bin to image format (2D matrix) 
img = zeros(num_ring, num_sector);

min_num_thres = 5; % a bin with few points, we consider it is noise.

% Find maximum Z value of each bin and Save into img 
for ith_ring = 1:num_ring
    for ith_sector = 1:num_sector
        value_of_the_bin = 0;            
        points_in_bin_ij = cell_bins{ith_ring, ith_sector};

        if( IsBinHaveMoreThanMinimumPoints(points_in_bin_ij, min_num_thres, enough_small) )
            value_of_the_bin = max(points_in_bin_ij(:, 3));
        else
            value_of_the_bin = 0;      
        end
        
        img(ith_ring, ith_sector) = value_of_the_bin;    
    end
end


end % end of the main function 


function bool = IsBinHaveMoreThanMinimumPoints(mat, minimum_thres, enough_small)

min_thres_point = mat(minimum_thres, :);

if( isequal(min_thres_point, [ enough_small, enough_small, enough_small]) )
    bool = 0;
else
    bool = 1;
end

end