High Dynamic Range Imaging
This example shows how to generate HDL code from a MATLAB® design that implements a high dynamic range imaging algorithm.
Algorithm
High Dynamic Range Imaging (HDRI or HDR) is a set of methods used in imaging and photography to allow a greater dynamic range between the lightest and darkest areas of an image than current standard digital imaging methods or photographic methods. HDR images can represent more accurately the range of intensity levels found in real scenes, from direct sunlight to faint starlight, and is often captured by way of a plurality of differently exposed pictures of the same subject matter.
MATLAB Design
design_name = 'mlhdlc_hdr'; testbench_name = 'mlhdlc_hdr_tb';
Use the dbtype function to display the contents of the MATLAB design.
dbtype(design_name);
1 function [valid_out, x_out, y_out, ... 2 HDR1, HDR2, HDR3] = mlhdlc_hdr(YShort1, YShort2, YShort3, ... 3 YLong1, YLong2, YLong3, ... 4 plot_y_short_in, plot_y_long_in, ... 5 valid_in, x, y) 6 % 7 8 % Copyright 2013-2015 The MathWorks, Inc. 9 10 % This design implements a high dynamic range imaging algorithm. 11 12 plot_y_short = plot_y_short_in; 13 plot_y_long = plot_y_long_in; 14 15 %% Apply Lum(Y) channels LUTs 16 y_short = plot_y_short(uint8(YShort1)+1); 17 y_long = plot_y_long(uint8(YLong1)+1); 18 19 y_HDR = (y_short+y_long); 20 21 %% Create HDR Chorm channels 22 % HDR per color 23 24 HDR1 = y_HDR * 2^-8; 25 HDR2 = (YShort2+YLong2) * 2^-1; 26 HDR3 = (YShort3+YLong3) * 2^-1; 27 28 %% Pass on valid signal and pixel location 29 30 valid_out = valid_in; 31 x_out = x; 32 y_out = y; 33 34 end
dbtype(testbench_name);
1
2 %
3
4 % Copyright 2013-2015 The MathWorks, Inc.
5
6 % Clean screen and memory
7 close all
8 clear mlhdlc_hdr
9 set(0,'DefaultFigureWindowStyle','docked')
10
11
12 %% Read the two exposed images
13
14 short = imread('mlhdlc_hdr_short.tif');
15 long = imread('mlhdlc_hdr_long.tif');
16
17 % define HDR output variable
18 HDR = zeros(size(short));
19 [height, width, color] = size(HDR);
20
21 set(0,'DefaultFigureWindowStyle' , 'normal')
22 figure('Name', [mfilename, '_plot']);
23 subplot(1,3,1);
24 imshow(short, 'InitialMagnification','fit'), title('short');
25
26 subplot(1,3,2);
27 imshow(long, 'InitialMagnification','fit'), title('long');
28
29
30 %% Create the Lum(Y) channels LUTs
31 % Pre-process
32 % Luminance short LUT
33 ShortLut.x = [0 16 45 96 255];
34 ShortLut.y = [0 20 38 58 115];
35
36 % Luminance long LUT
37 LongLut.x = [ 0 255];
38 LongLut.y = [ 0 140];
39
40 % Take the same points to plot the joined Lum LUT
41 plot_x = 0:1:255;
42 plot_y_short = interp1(ShortLut.x,ShortLut.y,plot_x); %LUT short
43 plot_y_long = interp1(LongLut.x,LongLut.y,plot_x); %LUT long
44
45 %subplot(4,1,3);
46 %plot(plot_x, plot_y_short, plot_x, plot_y_long, plot_x, (plot_y_long+plot_y_short)), grid on;
47
48
49 %% Create the HDR Lum channel
50 % The HDR algorithm
51 % read the Y channels
52
53 YIQ_short = rgb2ntsc(short);
54 YIQ_long = rgb2ntsc(long);
55
56 %% Stream image through HDR algorithm
57
58 for x=1:width
59 for y=1:height
60 YShort1 = round(YIQ_short(y,x,1)*255); %input short
61 YLong1 = round(YIQ_long(y,x,1)*255); %input long
62
63 YShort2 = YIQ_short(y,x,2); %input short
64 YLong2 = YIQ_long(y,x,2); %input long
65
66 YShort3 = YIQ_short(y,x,3); %input short
67 YLong3 = YIQ_long(y,x,3); %input long
68
69 valid_in = 1;
70
71 [valid_out, x_out, y_out, HDR1, HDR2, HDR3] = mlhdlc_hdr(YShort1, YShort2, YShort3, YLong1, YLong2, YLong3, plot_y_short, plot_y_long, valid_in, x, y);
72
73 % use x and y to reconstruct image
74 if valid_out == 1
75 HDR(y_out,x_out,1) = HDR1;
76 HDR(y_out,x_out,2) = HDR2;
77 HDR(y_out,x_out,3) = HDR3;
78 end
79 end
80 end
81
82 %% plot HDR
83 HDR_rgb = ntsc2rgb(HDR);
84 subplot(1,3,3);
85 imshow(HDR_rgb, 'InitialMagnification','fit'), title('hdr ');
Simulate the Design
It is always a good practice to simulate the design with the testbench prior to code generation to make sure there are no runtime errors.
mlhdlc_hdr_tb
Create a New HDL Coder™ Project
coder -hdlcoder -new mlhdlc_hdr_prj
Next, add the file 'mlhdlc_hdr.m' to the project as the MATLAB Function and 'mlhdlc_hdr_tb.m' as the MATLAB Test Bench.
Refer to Get Started with MATLAB to HDL Workflow for a more complete tutorial on creating and populating MATLAB HDL Coder projects.
Creating Constant Parameter Inputs
This example shows to use pass constant parameter inputs.
In this design the input parameters 'plot_y_short_in' and 'plot_y_long_in' are constant input parameters. You can define them accordingly by modifying the input types as 'constant(double(1x256))'
'plot_y_short_in' and 'plot_y_short_in' are LUT inputs. They are constant folded as double inputs to the design. You will not see port declarations for these two input parameters in the generated HDL code.
Note that inside the design 'mlhdlc_hdr.m' these variables are reassigned so that they get properly fixed-point converted. This is not necessary if these are purely used as constants for defining sizes of variables for example and not part of the logic.
Run Fixed-Point Conversion and HDL Code Generation
Launch HDL Advisor and right click on the 'Code Generation' step and choose the option 'Run to selected task' to run all the steps from the beginning through the HDL code generation.
Convert the Design to Fixed-Point and Generate HDL Code
The following script converts the design to fixed-point, and generate HDL code with a test bench.
exArgs = {0,0,0,0,0,0,coder.Constant(ones(1,256)),coder.Constant(ones(1,256)),0,0,0};
fc = coder.config('fixpt');
fc.TestBenchName = 'mlhdlc_hdr_tb';
hc = coder.config('hdl');
hc.GenerateHDLTestBench = true;
hc.SimulationIterationLimit = 1000; % Limit number of testbench points
codegen -float2fixed fc -config hc -args exArgs mlhdlc_hdrExamine the generated HDL code by clicking on the hyperlinks in the Code Generation Log window.
