Need to add additional filter to support Landsat 7 SLC-off imagery

[alex-s-gardner]

In the initial preprocessing of the imagery (e.g. application of the Wallis filter) we need to add an option for L7 filtering which requires filling the missing data stripes with random noise that as the same mean and std as the filtered valid L7 imagery. Below is the prototype code written in Matlab:

% add random noise to SLC_off imagery % Landsat 7 data aquired AFTER 2003, 5, 31

%% ----------------- READ IN IMAGERY --------------------- % check if image is ETM+ SLC-off I = imread('data/LE07_L1TP_009011_20130809_20200907_02_T1_B8.tif'); I = single(I);

WallisFilterWidth = 5; % filter width <- already implemented in autoRIFT StandardDeviationCutoff = 0.25; <- already implemented in autoRIFT

%% ----------------- START OF NEW FILTER --------------------- % make random number generator unique ImNoData = 0; rng(round(sum(pwd)+now*100),'twister');

% buffer values lines by sqrt(((filtWidth-1)/2)^2) + 0.01 for % rounding buff = sqrt(2*((WallisFilterWidth-1)/2)^2) + 0.01;

validDomain = I ~= ImNoData; % validDomain is the image frame ImNoData = single(ImNoData);

% find edges of image, this makes missing scan lines valid and will % later be filled with random white noise missingData = bwdist(validDomain,'euclidean')<30; % missingData is missing data within image frame missingData = missingData & ~validDomain; missingData = bwdist(missingData,'euclidean')<= buff;

% trying to frame out the image validDomain = validDomain | missingData;

LowStd = stdfilt(I, ones(WallisFilterWidth))<StandardDeviationCutoff; LowStd = bwdist(LowStd,'euclidean')<= buff; missingData(:,:,1) = (missingData(:,:,1) | LowStd) & validDomain;

%% ----------------- This is already coded in autoRIFT ----------------- % apply high pass filter colFiltParallel = true; fun = @(block_struct) wallis_filt(block_struct.data, WallisFilterWidth); I = blockproc(I,[10000 10000], fun, ... 'BorderSize', [WallisFilterWidth, WallisFilterWidth],'PadPartialBlocks', ... false, 'TrimBorder', true, 'UseParallel', colFiltParallel);

% if scan line corrector off image % scale to fit range of int8

validData = validDomain & ~missingData; I(~validData) = 0;

% populate random values with same std and mean fillData = validDomain & missingData; R = randn([sum(fillData(:)),1]); I(fillData) = R;