В этом примере показано, как сгенерировать HDL-код из проекта MATLAB®, который настраивает контрастность изображений путем линейного масштабирования пиксельных значений.
Контрастная корректировка настраивает контраст изображения путем линейного масштабирования пиксельных значений между верхним и нижними пределами. Пиксельные значения, которые являются выше или ниже этой области значений, насыщаются к верхнему значению или значению нижнего предела, соответственно.
design_name = 'mlhdlc_image_scale'; testbench_name = 'mlhdlc_image_scale_tb';
Давайте смотреть на проект MATLAB
type(design_name);
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % scale.m % % Adjust image contrast by linearly scaling pixel values. % % The input pixel value range has 14bits and output pixel value range is % 8bits. % %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% function [x_out, y_out, pixel_out] = ... mlhdlc_image_scale(x_in, y_in, pixel_in, ... damping_factor_in, dynamic_range_in, ... tail_size_in, max_gain_in, ... width, height) % Copyright 2011-2015 The MathWorks, Inc. persistent histogram1 histogram2 persistent low_count persistent high_count persistent offset persistent gain persistent limits_done persistent damping_done persistent reset_hist_done persistent scaling_done persistent hist_ind persistent tail_high persistent min_hist_damped %Damped lower limit of populated histogram persistent max_hist_damped %Damped upper limit of populated histogram persistent found_high persistent found_low DR_PER_BIN = 8; SF = 1./(1:(2^14/8)); % be nice to fix this NR_OF_BINS = (2^14/DR_PER_BIN) - 1; MAX_DF = 255; if isempty(offset) offset = 1; gain = 1; limits_done = 1; damping_done = 1; reset_hist_done = 1; scaling_done = 1; hist_ind = 1; tail_high = NR_OF_BINS; low_count = 0; high_count = 0; min_hist_damped = 0; max_hist_damped = (2^14/DR_PER_BIN) - 1; found_high = 0; found_low = 0; end if isempty(histogram1) histogram1 = zeros(1, NR_OF_BINS+1); histogram2 = zeros(1, NR_OF_BINS+1); end if y_in < height frame_valid = 1; if x_in < width line_valid = 1; else line_valid = 0; end else frame_valid = 0; line_valid = 0; end % initialize at beginning of frame if x_in == 0 && y_in == 0 limits_done = 0; damping_done = 0; reset_hist_done = 0; scaling_done = 0; low_count = 0; high_count = 0; hist_ind = 1; end max_gain_frac = max_gain_in/2^4; pix11 = floor(pixel_in/DR_PER_BIN); pix_out_temp = pixel_in; %************************************************************************** %Check if valid part of frame. If pixel is valid remap pixel to desired %output dynamic range (dynamic_range_in) by subtracting the damped offset %(min_hist_damped) and applying the calculated gain calculated from the %previous frame histogram statistics. %************************************************************************** % histogram read histReadIndex1 = 1; histReadIndex2 = 1; if frame_valid && line_valid histReadIndex1 = pix11+1; histReadIndex2 = pix11+1; elseif ~limits_done histReadIndex1 = hist_ind; histReadIndex2 = NR_OF_BINS - hist_ind; end histReadValue1 = histogram1(histReadIndex1); histReadValue2 = histogram2(histReadIndex2); histWriteIndex1 = NR_OF_BINS+1; histWriteIndex2 = NR_OF_BINS+1; histWriteValue1 = 0; histWriteValue2 = 0; if frame_valid if line_valid temp_sum = histReadValue1 + 1; ind = min(pix11+1, NR_OF_BINS); val = min(temp_sum, tail_size_in); histWriteIndex1 = ind; histWriteValue1 = val; histWriteIndex2 = ind; histWriteValue2 = val; %Scale pixel pix_out_offs_corr = pixel_in - min_hist_damped*DR_PER_BIN; pix_out_scaled = pix_out_offs_corr * gain; pix_out_clamp = max(min(dynamic_range_in, pix_out_scaled), 0); pix_out_temp = pix_out_clamp; end else %********************************************************************** %Ignore tail_size_in pixels and find lower and upper limits of the %histogram. %********************************************************************** if ~limits_done if hist_ind == 1 tail_high = NR_OF_BINS-1; offset = 1; found_high = 0; found_low = 0; end low_count = low_count + histReadValue1; hist_ind_high = NR_OF_BINS - hist_ind; high_count = high_count + histReadValue2; %Found enough high outliers if high_count > tail_size_in && ~found_high tail_high = hist_ind_high; found_high = 1; end %Found enough low outliers if low_count > tail_size_in && ~found_low offset = hist_ind; found_low = 1; end hist_ind = hist_ind + 1; %All bins checked so limits must already be found if hist_ind >= NR_OF_BINS hist_ind = 1; limits_done = 1; end %********************************************************************** %Damp the limit change to avoid image flickering. Code below equivalent %to: max_hist_damped = damping_factor_in*max_hist_dampedOld + %(1-damping_factor_in)*max_hist_dampedNew; %********************************************************************** elseif ~damping_done min_hist_weighted_old = damping_factor_in*min_hist_damped; min_hist_weighted_new = (MAX_DF-damping_factor_in+1)*offset; min_hist_weighted = (min_hist_weighted_old + ... min_hist_weighted_new)/256; min_hist_damped = max(0, min_hist_weighted); max_hist_weighted_old = damping_factor_in*max_hist_damped; max_hist_weighted_new = (MAX_DF-damping_factor_in+1)*tail_high; max_hist_weighted = (max_hist_weighted_old + ... max_hist_weighted_new)/256; max_hist_damped = min(NR_OF_BINS, max_hist_weighted); damping_done = 1; hist_ind = 1; %********************************************************************** %Reset all bins to zero. More than one bin can be reset per function %call if blanking time is too short. %********************************************************************** elseif ~reset_hist_done histWriteIndex1 = hist_ind; histWriteValue1 = 0; histWriteIndex2 = hist_ind; histWriteValue2 = 0; hist_ind = hist_ind+1; if hist_ind == NR_OF_BINS reset_hist_done = 1; end %********************************************************************** %The gain factor is determined by comparing the measured damped actual %dynamic range to the desired user specified dynamic range. Input %dynamic range is measured in bins over DR_PER_BIN space. %********************************************************************** elseif ~scaling_done dr_in = round(max_hist_damped - min_hist_damped); gain_temp = dynamic_range_in*SF(dr_in); gain_scaled = gain_temp/DR_PER_BIN; gain = min(max_gain_frac, gain_scaled); scaling_done = 1; hist_ind = 1; end end histogram1(histWriteIndex1) = histWriteValue1; histogram2(histWriteIndex2) = histWriteValue2; x_out = x_in; y_out = y_in; pixel_out = pix_out_temp;
type(testbench_name);
%Test bench for scaling, analogous to automatic gain control (AGC) % Copyright 2011-2018 The MathWorks, Inc. testFile = 'mlhdlc_img_peppers.png'; imgOrig = imread(testFile); [height, width] = size(imgOrig); imgOut = zeros(height,width); hBlank = 20; % make sure we have enough vertical blanking to filter the histogram vBlank = ceil(2^14/(width+hBlank)); %df - Temporal damping factor of rescaling %dr - Desired output dynamic range df = 0; dr = 255; nrOfOutliers = 248; maxGain = 2*2^4; for frame = 1:2 disp(['frame: ', num2str(frame)]); for y_in = 0:height+vBlank-1 %disp(['frame: ', num2str(frame), ' of 2, row: ', num2str(y_in)]); for x_in = 0:width+hBlank-1 if x_in < width && y_in < height pixel_in = double(imgOrig(y_in+1, x_in+1)); else pixel_in = 0; end [x_out, y_out, pixel_out] = ... mlhdlc_image_scale(x_in, y_in, pixel_in, df, dr, ... nrOfOutliers, maxGain, width, height); if x_out < width && y_out < height imgOut(y_out+1,x_out+1) = pixel_out; end end end figure('Name', [mfilename, '_scale_plot']); imgOut = round(255*imgOut/max(max(imgOut))); subplot(2,2,1); imshow(imgOrig, []); title('Original Image'); subplot(2,2,2); imshow(imgOut, []); title('Scaled Image'); subplot(2,2,3); histogram(double(imgOrig(:)),2^14-1); axis([0, 255, 0, 1500]); title('Histogram of original Image'); subplot(2,2,4); histogram(double(imgOut(:)),2^14-1); axis([0, 255, 0, 1500]); title('Histogram of equalized Image'); end
Это - хорошая практика, чтобы симулировать проект с испытательным стендом до генерации кода, чтобы убедиться, что нет никаких ошибок периода выполнения.
mlhdlc_image_scale_tb
frame: 1 frame: 2
Выполните следующие строки кода, чтобы скопировать необходимые файлы в качестве примера во временную папку.
mlhdlc_demo_dir = fullfile(matlabroot, 'toolbox', 'hdlcoder', 'hdlcoderdemos', 'matlabhdlcoderdemos'); mlhdlc_temp_dir = [tempdir 'mlhdlc_scale']; % create a temporary folder and copy the MATLAB files cd(tempdir); [~, ~, ~] = rmdir(mlhdlc_temp_dir, 's'); mkdir(mlhdlc_temp_dir); cd(mlhdlc_temp_dir); % copy files to the temp dir copyfile(fullfile(mlhdlc_demo_dir, [design_name,'.m*']), mlhdlc_temp_dir); copyfile(fullfile(mlhdlc_demo_dir, [testbench_name,'.m*']), mlhdlc_temp_dir); copyfile(fullfile(mlhdlc_demo_dir, 'mlhdlc_img_peppers.png'), mlhdlc_temp_dir);
coder -hdlcoder -new mlhdlc_scale_prj
Затем добавьте файл 'mlhdlc_image_scale.m' в проект как функция MATLAB и 'mlhdlc_image_scale_tb.m' как Испытательный стенд MATLAB.
Можно обратиться к Началу работы с MATLAB к примеру по Рабочему процессу HDL для более полного примера при создании и заполнении проектов HDL Coder MATLAB.
Запустите Советника по вопросам Рабочего процесса от вкладки Build, и щелчок правой кнопкой по 'Генерации кода' продвигаются и выбирают опцию, 'Запущенную к выбранной задаче', чтобы запустить все шаги с начала через генерацию HDL-кода.
Исследуйте сгенерированный HDL-код путем нажатия на гиперссылки в окне Code Generation Log.
Можно запустить следующие команды, чтобы очистить временную папку проекта.
mlhdlc_demo_dir = fullfile(matlabroot, 'toolbox', 'hdlcoder', 'hdlcoderdemos', 'matlabhdlcoderdemos'); mlhdlc_temp_dir = [tempdir 'mlhdlc_scale']; clear mex; cd (mlhdlc_demo_dir); rmdir(mlhdlc_temp_dir, 's');